1695 results about "Surface reflection" patented technology

The invention discloses an intelligent positioning method and system for can making stamping, and relates to the technical field of image processing. Comprising the following steps: acquiring a tank stamping part image, and segmenting the tank stamping part from a background by adopting a self-adaptive threshold segmentation algorithm to obtain segmented tank region image data; utilizing a moment-based sub-pixel edge detection method to accurately position the edge coordinates of the contour of the tank body, and obtaining the key dimension parameters of the tank body; extracting texture features of the surface of the tank body by adopting a gray-level co-occurrence matrix and a local binary pattern algorithm, and judging whether the texture features belong to surface defects or not through a support vector machine classification model; the method solves the problem that edge information is difficult to accurately extract when a traditional image processing method faces tank surface reflection and a complex background, ensures the accuracy of a measurement result by establishing a tank coordinate system and performing attitude correction, overcomes the problem that the tank is easy to deviate or incline in the production process, and improves the production efficiency. And high-efficiency and accurate quality detection of the tank stamping part is realized.

The invention provides an aluminum alloy surface oxidation spot defect identification method and device based on machine vision, and relates to the field of intelligent manufacturing and industrial automation, and the method comprises the steps: obtaining an aluminum alloy surface color image, and carrying out the preprocessing of the image, so as to extract a brightness component image; self-adaptive threshold segmentation of local contrast enhancement is carried out on the brightness component image, a defect area binary mask is generated, morphological connected domains are extracted according to the mask, and three basic feature indexes of the area pixel value, the contour Fourier descriptor complexity and the area gray scale standard deviation contrast of each connected domain are calculated; and extracting and marking a connected domain boundary, verifying a boundary closed topological structure, and dynamically generating a curvature-driven self-adaptive sampling point through multi-scale B-spline curvature extreme value detection. Through optical-algorithm-process three-level collaborative innovation, the curved surface reflection false alarm rate is reduced, the pinhole detection rate is increased, and the boundary precision is + / -0.2 pixel.

The invention discloses an egg surface microcrack detection system and method based on image analysis, and relates to the field of surface defect nondestructive detection.The method comprises the steps that a process identification interface module obtains a processing process identifier of an egg in real time; the multi-angle annular light source module is provided with a multi-band annular light source array comprising visible light and near-infrared LED lamp beads which are independently controlled, a polaroid group and a beam splitter prism are integrated, and visible light polarization images and near-infrared polarization images on the surfaces of the eggs are synchronously collected; the thermal excitation enhancement unit obtains a thermal infrared image; the process filtering module extracts the axial elongation of the mechanical stress microcrack after graded transportation, and calculates the mesh fractal dimension of the thermal stress microcrack after UV disinfection; the multi-modal feature fusion module generates a dual-channel crack probability graph; and the dynamic feedback control module outputs a micro-crack risk grade and adjusts the rotating speed of the objective table and the light source intensity. The method has the advantages that accurate judgment of mechanical and thermal stress cracks is realized, and curved surface reflection interference is broken through.

The invention provides an aluminum film sealing defect real-time detection method and system based on multi-algorithm fusion, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: triggering an industrial camera at a detection station to collect an original image of a pesticide aluminum film sealing on a conveyor belt; performing adaptive equalization operation on the original image through pixel brightness distribution data, eliminating light fluctuation and surface reflection interference, and outputting a standardized image; three types of defect detection are synchronously executed based on the standardized image, a dynamic threshold segmentation algorithm is combined with local area brightness analysis to detect edge damage, a contour extraction algorithm is adopted to calculate bottleneck center offset to recognize seal offset, wrinkle defects are recognized based on a surface texture feature analysis algorithm, and a primary detection result is output. The aluminum film sealing defect detection method is based on multi-algorithm fusion, has strong anti-interference capability, real-time detection performance and data traceability, and provides an efficient and reliable automatic solution for aluminum film sealing quality management and control.

The invention discloses a chip surface defect visual detection method and system, and the method comprises the steps: carrying out the high-sensitivity imaging through the dynamic adaptation of a quantum imaging enhancement module to the surface reflectivity, and achieving the sparse efficient processing of a defect signal through the combination of event-driven vision and a pulse neural network; based on a risk thermodynamic diagram generated in real time, intelligently scheduling detection precision and speed resources, and utilizing multi-modal feature decoupling and a federal knowledge graph to accurately associate defects and process roots; the digital twinning module synchronously predicts a defect evolution path and drives online adjustment and optimization of process parameters, and meanwhile the dynamic compensation module corrects optical defocus in real time. According to the invention, full-detection coverage of nanoscale defects is realized, a defect transfer chain is actively blocked while the detection efficiency is improved, and the chip manufacturing yield and reliability are remarkably improved.

The invention discloses a quality-graded remote sensing image composite cloud removal method, system and device. The method comprises the following steps: preprocessing an acquired remote sensing image; based on the preprocessed data, thin cloud radiation correction is carried out; based on the data after thin cloud radiation correction, thick cloud detection is carried out; based on the data after thick cloud detection, thick cloud missing reconstruction is carried out; performing atmospheric correction based on the data after the thick cloud missing reconstruction; and performing data quality grading based on the data after atmospheric correction. According to the method, a series of standardized processing is realized on data acquired under different space and time conditions, the influence of atmospheric radiation attenuation is eliminated, and the data are formatted into surface reflection data with consistent observation characteristics, so that the utilization rate of remote sensing images is improved, and effective comparison and analysis of subsequent application research are promoted.

The invention discloses a machine vision-based intelligent detection method for steel galvanized surface defects, which comprises the following steps: S1, acquiring and preprocessing a steel galvanized surface image to obtain a standardized image; s2, constructing a specular reflection probability graph according to the brightness distribution and the gradient magnitude, and calculating a reflection intensity value; s3, calculating a structure tensor matrix, determining a main direction angle and an anisotropic consistency coefficient, and generating a direction feature matrix; s4, establishing a multi-scale direction adaptive phase kernel function, and performing phase modulation in a frequency domain by adopting an improved phase stretching transformation algorithm; s5, inverse Fourier transform is executed, and a phase response matrix is extracted; s6, performing weighted fusion to obtain a comprehensive phase response diagram; and S7, setting a threshold value according to the noise variance and the statistical characteristics, executing binarization and morphological processing, and outputting a defect region and boundary coordinates. According to the invention, high-precision identification and boundary positioning of steel galvanized surface defects are realized.

The invention relates to the technical field of quality detection, in particular to a medical refrigerator body manufacturing detection system and method, and the system comprises a coating reflection detection module, a sound wave response measurement module, an optical signal fluctuation analysis module, a surface defect recognition module and a structural feature state evaluation module. According to the method, the reflection amplitude gradient change of the adjacent scanning areas is compared with the spectral curve continuity, so that the sensing precision of the surface reflection distribution continuity is improved, the recognition capability of weak anomalies is enhanced, and the internal potential defects are accurately captured in combination with the sound wave echo time and structural stability analysis of a specific part; a light intensity gradient model is constructed according to a sound wave analysis result, a splicing seam and a light intensity jump area of a sunken area are identified, abnormal forms such as scratches and bubbles are further extracted, coordinates are marked, the whole process depends on dynamic feedback and multi-signal linkage calibration, the identification precision and the coverage rate are improved, and medical box body quality global efficient detection is achieved.

Methods include generating a modulated light pattern using a light modulator (108), transmitting the modulated light pattern through an objective lens (104) to a surface of a substrate (150), where the objective lens (104) defines an object plane, obtaining a plurality of images of the modulated light pattern reflected from the surface of a substrate (150), where each modulated light pattern is obtained at a different relative distance between the objective lens (104) and the substrate surface, analyzing the plurality of images to determine a reference location of the substrate surface relative to the objective lens (104) that corresponds to positioning of an image of the modulated light pattern formed by the objective lens (104) at the object plane, and adjusting a position of the substrate (150) relative to the objective lens (104) based on the reference location.

A visual defect detection method, device, medium and product relate to the field of visual detection, and the method comprises the following steps: firstly, recording brightness changes of pixel points in different illumination directions by constructing an illumination response matrix, and establishing a complete mapping of surface reflection characteristics; secondly, performing joint calculation by using the light source direction matrix and the illumination response matrix to obtain normal vector data and reflectivity data, and representing spatial geometric features and material optical features of the surface respectively; thirdly, calculating a gradient feature map, a curvature feature map and a deformation feature map based on the normal vector data, generating a reflectivity map by using the reflectivity data, and forming a multi-dimensional feature representation system; and finally, in a defect detection stage, a strategy of combining gradient feature pre-screening with multi-feature verification is adopted, and final judgment is carried out by calculating a comprehensive defect feature value, so that the technical problem of insufficient micro defect detection precision of a visual detection method in the prior art is solved.

The invention relates to the technical field of image compensation, in particular to a reflection compensation method based on image processing, and provides the following scheme: acquiring an environment panoramic image by using a panoramic camera to establish a scene global coordinate system, and acquiring a multi-view original image in combination with a camera array arranged in the circumferential direction of an object; determining a rotation symmetry axis according to the multi-view contour features, reconstructing a three-dimensional geometric body, and calculating normal distribution and curvature change; generating a prediction image based on diffuse reflection and specular reflection hypothesis in the surface expansion domain through virtual visual angle disturbance, identifying a reflection region according to color and gradient consistency, and generating a reflection mask; and performing texture reconstruction on the reflective area by using geometric registration and multi-view compensation, and finally performing splicing and fusion to obtain a non-reflective high-fidelity panoramic image. The method does not need to change the field illumination condition, and can achieve the precise recognition and compensation of the complex curved surface reflection in the cultural relic in-situ collection environment.

The invention discloses an optical fiber Fabry-Perot sensor for detecting C4F7N gas and decomposition products thereof, belongs to the technical field of C4F7N gas detection, and solves the problem of how to improve the sensitivity of the optical fiber Fabry-Perot sensor for detecting the C4F7N gas and the decomposition products thereof. According to the optical fiber Fabry-Perot sensor for detecting the C4F7N gas and the decomposition products thereof, the Fabry-Perot cavity is formed by the interval between the end face of the single-mode optical fiber and the surface of the groove, emergent light of the single-mode optical fiber is reflected by the surface of the groove, the reflected light is converged by the groove, the loss of the reflected light is reduced, and the detection accuracy of the C4F7N gas and the decomposition products thereof is improved. Gold is uniformly sputtered on one surface of the groove of the sensing diaphragm device layer to form a layer of reflecting film, so that the reflectivity is further improved, reflected light is efficiently coupled into the single-mode optical fiber, the contrast ratio of a light interference peak is improved, and the detection sensitivity of the sensor is further improved; the sensor is simple in structure, small in size, high in reliability and capable of achieving high-sensitivity measurement of the C4F7N gas decomposition products.

A system for three-dimensional spatial perception underwater that includes a primary submersible vehicle. Frontward facing projectors are used to scan beams of light across a selected field of underwater view. Further, event cameras with pixels triggered by events are used to detect corresponding spots of the scanned beams that are reflected from underwater objects or surfaces. Circuitry is configured to determine positions of the objects based on the pixels that are triggered. Additionally, pilot submersible vehicles the projectors and event cameras are tethered to the primary submersible vehicle to provide extend detection of spots corresponding to reflections from underwater objects or surfaces.

The invention discloses a C4F7N gas optical fiber Fabry-Perot sensor, a sensitivity demodulation system and a sensitivity demodulation method, belongs to the technical field of C4F7N gas detection, and solves the problem of how to improve the sensitivity of the C4F7N gas optical fiber Fabry-Perot sensor. A Fabry-Perot cavity is formed by a gap between the end face of a single-mode optical fiber of the C4F7N gas optical fiber Fabry-Perot sensor and the surface of a groove; emergent light of the single-mode optical fiber is reflected by the surface of the groove, and the groove converges the reflected light, so that the loss of the reflected light is reduced, and the detection sensitivity of the sensor is improved; the sensor is simple in structure, small in size and high in reliability; according to the sensitivity demodulation system, the resonant wavelength drift direction is judged based on a twice multi-frequency correlation demodulation method, and then the sensitivity of the sensor is represented according to a peak value tracking method; the cavity length of the sensor can be demodulated by only one enveloped wavelength range, so that the requirement on the bandwidth of a light source is reduced, and the equipment investment cost is reduced.

The invention provides a door and window glass defect feedback control method and device, electronic equipment and a storage medium, and relates to the technical field of door and window glass defect detection. The method comprises the steps of collecting a first image after a polarized light imaging detection device is adjusted to suppress reflected light on the surface of glass and enhance scattered light of bubbles in the glass; after the polarized light imaging detection device is adjusted to enhance reflected light on the glass surface, a second image is collected; calculating an adaptive weight group by analyzing local characteristics of the second image; weighting the first image according to the self-adaptive weight group, and subtracting the weighted first image from the second image to obtain a difference image; and extracting bubble defect information in the glass by analyzing the differential image. According to the method, interference caused by non-uniformity of glass surface reflection is overcome, the adaptability of image differential processing to surface reflection background suppression is improved, and therefore image features of internal bubble defects are extracted more effectively and more accurately.

The invention relates to the technical field of hydrological survey, in particular to a water level photography monitoring method and device for eliminating water surface inverted image interference, and the method comprises the steps: carrying out the distortion correction of an original water gauge image, and obtaining a distortion correction image; classifying the distortion correction images to obtain day and night classification images; performing water surface line detection on the day and night classification images, identifying an initial water surface line, and correcting the initial water surface line to obtain a corrected water surface line; adaptively positioning a water gauge foreground prompt point and a non-water gauge background prompt point based on the corrected water surface line; inputting the day and night classification image, the water gauge foreground prompt point and the non-water gauge background prompt point into an SAM image segmentation model based on a cross attention mechanism to obtain a water gauge mask segmentation result; and obtaining the water level of the water body according to the water gauge mask segmentation result and the water level identification model. Real-time monitoring of the water level of the water body is achieved through the technologies of the self-adaptive prompt points, the image segmentation model and the like, and interference of water surface reflection on water level measurement is effectively overcome.

The invention provides a digital twin model correction method and system based on machine vision. The method comprises the steps that a comprehensive data set is constructed by collecting sounding data, tidal flow velocity data and unmanned aerial vehicle images, wave disturbance deviation and water surface reflection distortion are eliminated based on geometric feature matching, and a dynamic compensation coefficient is generated in combination with tidal parameters; after time deviation of sounding data is corrected, a dynamic incidence relation between terrain elevation and sediment migration rate is calculated, a digital twinborn model fusing sedimentary layer thickness distribution and tidal flow velocity driven erosion boundary prediction is established, and a visual terrain curved surface is generated; through reverse verification of real-time sediment accumulation characteristics and terrain curved surfaces, migration rate weight parameters are adjusted in a self-adaptive mode, and dynamic optimization of the model is achieved. High-precision dynamic coupling simulation of sea area terrain evolution and sediment migration is achieved, the real-time performance and reliability of island surface change prediction are improved, and coastal zone safety and economic collaborative decision making is supported.

The invention discloses a fish school counting method based on density map regression. The method comprises the following steps: S1, constructing fish school data sets with different densities; step S2, constructing a U-Fish network architecture; s3, constructing a U-Fish loss function; s4, using an image enhancement method to optimize the image quality, mixing the original image with the enhanced image to train the established U-Fish model, and obtaining a fish school counting model after training; and S5, inputting a to-be-detected image and a corresponding enhanced image into the trained fish school counting model, and outputting a density map and a counting result by the model. According to the method, the influence caused by water surface reflection and fish school overlapping can be effectively overcome, the counting precision is improved, and the complexity of model calculation is reduced.

The invention relates to the technical field of defect detection, and particularly discloses an electronic component defect detection method, system and device, and the method comprises the steps: collecting a multiband original image set based on multispectral imaging, inhibiting batch material difference and surface reflection through orthogonal complementary space projection, and obtaining a de-noised image set; performing feature extraction on the de-noised image set, and identifying and marking all fragmented defect areas; based on a graph neural network space attention mechanism, establishing an association relationship between fragmented defect areas to form a complete defect feature chain; gray frequency value sequences of the to-be-detected image and the standard sample image are constructed respectively, and a first fitting curve and a second fitting curve are obtained through fitting of a skewed distribution function; and finally, comprehensively judging whether the electronic component has defects or not by combining the defect characteristic chain and the difference characteristics of the two fitting curves. According to the method, interference can be effectively suppressed, fragmented defects can be accurately identified, and the detection accuracy and reliability are remarkably improved through multi-dimensional feature fusion.

The invention discloses a data processing method and system for a dental three-dimensional model, and relates to the technical field of dental three-dimensional modeling, and the method comprises the steps: obtaining initial data of oral cavity scanning, recognizing a tooth type in the initial data, and determining a corresponding tooth surface reflection parameter according to the tooth type; generating scanning parameter combinations for different tooth positions according to the tooth surface reflection parameters and the tooth anatomical structure; tooth point cloud data are collected, and a tooth enamel reflective area and a shadow shielding area are identified; performing light reflection removal processing on the enamel light reflection area, performing data completion on the shadow shielding area, and generating corrected tooth point cloud data; and performing registration fusion on the corrected tooth point cloud data to generate a dental three-dimensional model containing a complete dentition. According to the method, the problem of data missing caused by enamel light reflection and adjacent tooth shielding is solved through a differential scanning strategy and regional data processing aiming at specific optical characteristics of teeth, and automatic construction of a high-quality dental three-dimensional model is realized.

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 belongs to the technical field of digital holographic measurement, and particularly relates to an optical element stress measurement and defect identification method based on a digital holographic photoelastic method. The method is realized based on a transmission-type off-axis digital holographic light path system; light beams emitted by the laser assembly are divided into reference light and object light, the object light is reflected by the surface of a sample and carries sample information, the object light and the reference light intersect in front of the CMOS camera to generate interference, the CMOS converts an interference light intensity signal into an electric signal, and holographic image processing is performed by the computer; the hologram before and after external force loading is reconstructed to obtain surface topography distribution, and the reconstruction precision is improved through the steps of positive first-order spectrum extraction, angular spectrum reconstruction automatic focusing and the like; the phase difference before and after external force loading is calculated through reconstruction complex amplitude phase extraction, and then the direction and size distribution of the principal stress of the sample are measured and calculated based on a digital photoelastic method and a stress optical law; and the defect of the optical element is identified by measuring the stress value change under the same external force loading, so that the method has important practical significance.

The invention provides a process detection method and system for an electronic connector pin, and the method comprises the steps: obtaining the inclined plane image data of the pin, carrying out the preprocessing according to the surface reflection characteristics of the pin and environment illumination interference, and obtaining a clear inclined plane image; applying an edge detection algorithm to the clear inclined plane image, and extracting inclined plane contour data including contact pin inclined plane features; according to the inclined plane contour data, inclined plane angle deviation is calculated, and whether the inclined plane angle deviation exceeds a preset angle deviation threshold value or not is judged; when the inclined plane angle deviation exceeds a preset angle deviation threshold value, obtaining the insertion depth and contact position data of the pin; performing correlation analysis on the slope angle deviation, the insertion depth and the contact position data, judging the influence of the slope angle deviation on the insertion depth and the contact position, and obtaining a correlation analysis result; and according to a correlation analysis result, adjusting pin processing technological parameters and re-processing the pin. Precise control of the inclined plane angle of the contact pin is realized, and the insertion performance and the contact reliability of the contact pin are improved.

The invention discloses a metal processing detection system and method based on computer vision, and relates to the technical field of defect detection.Rotatable polarization filters are installed in front of a lens of a vision sensor, the polarization filters are arranged at four angles respectively, and four sets of polarization images are collected; calculating the polarization degree of each pixel point on the surface during metal processing by using the gray values of the four groups of polarization images, setting a polarization region interval, and dividing a metal surface reflection region into a specular reflection region and a diffuse reflection region; acquiring images of different wavebands by using a multispectral vision sensor, and constructing a multispectral image set; for the same wave band, the images of different exposure times are synthesized to obtain an HDR high dynamic range image; setting a weight for the HDR image of each wave band, and combining the weighting of the HDR image and the suppression of the polarization degree to carry out multispectral image fusion so as to obtain a final image; and a gray threshold value and an area threshold value are respectively calculated through the average value and the standard deviation, and the metal processing defects are judged by using the two threshold values.

The invention provides a laser surface treatment method, device and equipment based on visual control, and the method comprises the steps: carrying out the energy waveform capture processing of pulse laser outputted by laser marking equipment, and carrying out the multi-channel visual detection of a surface reflection region of a to-be-marked part based on a pulse energy reference, and obtaining the surface feature information; planning an initial scanning path according to the surface feature information, and synchronously correcting a trigger time sequence of the pulse laser to obtain a target marking path; and in combination with the target marking path and the pulse energy reference, dynamic observation and local heat dispersion treatment are conducted on the marking area, and the treated part surface is obtained. The method is suitable for performing fine marking on a high-reflectivity or complex geometric surface, and can perform timely adjustment according to local temperature rise or optical characteristic change in the marking process to reduce depth unevenness and thermal damage.

The invention discloses a melamine paper surface defect detection system based on optical detection, and relates to the technical field of industrial optical detection, and the melamine paper surface defect detection system comprises a polarized light signal generation module which employs a high color rendering index white light source to irradiate the surface of melamine paper, obtains a surface reflection light beam array carrying different polarization states, and modulates the surface reflection light beam array into eight groups of independent polarized light signals; the multispectral imaging and registering module inputs eight groups of independent polarized light signals into a free-form surface prism group and performs light splitting to generate a diffuse reflection texture image, a mirror reflection image and a near-infrared perspective image, and constructs a three-channel space registering image matrix; and the light path calibration module is used for extracting defect coordinate data and confidence score based on the pixel-level defect thermodynamic image, and performing light path compensation by adopting a real-time feedback regulation mechanism to obtain a dynamically calibrated stable optical imaging signal.

The embodiment of the invention provides an optical module and near-to-eye display equipment. The optical module is used for XR optical equipment and comprises a cemented prism, a lens and a curved surface reflection element, and the lens is located between the cemented prism and the curved surface reflection element. The glued prism comprises a first prism and a second prism which are glued with each other, and the second prism and the lens are adjacent and are arranged at an interval; the curved surface reflection element comprises a sixth surface, the sixth surface is adjacent to the lens, and the sixth surface is a curved surface and is a partial reflection surface; the optical module further comprises a polarization reflection element and a phase delayer, the polarization reflection element is located between the first prism and the second prism, and the phase delayer is located between the second prism and the lens. The optical module meets the condition that EFL15 / EFL6 is larger than or equal to 0.2 and smaller than or equal to 4.1, EFL15 is the total effective focal length of the cemented prism and the lens, and EFL6 is the effective focal length of the curved surface reflection element.

The invention relates to a rice growth process three-dimensional scene construction method based on a crop growth model and a rendering engine, and the method comprises the following steps: obtaining plant density, distribution, leaf inclination angle distribution, a leaf spectrum, a canopy spectrum and substrate reflectivity through a field experiment, and constructing a single-plant rice 3D model; coupling a crop growth model, and describing vegetation canopy reflection characteristics through canopy structure parameters and leaf BRDF to simulate canopy reflection factors; respectively calculating a water body scattering phase function and a water surface BRDF according to the water body biological optical model and the wave water surface reflection model; generating a three-dimensional water body volume model through an AVRM model; blender software is combined with a LuxCoreRender rendering engine to couple incident radiation, vegetation canopy reflection factors, water optical attributes and other related input parameters, and a real rice scene is constructed. According to the method, the high-precision three-dimensional rice scene model is established, important technical support is provided for improving the precision and efficiency of rice remote sensing radiation modeling and further for agricultural remote sensing and wetland monitoring, and the method has popularization and application prospects.

The invention relates to the technical field of acoustic imaging, and relates to a phase holographic imaging device based on an acoustic metamaterial, which comprises a sound wave generator, an LAM metasurface and a control unit, the sound generator is used for generating plane sound waves; the LAM metasurface is used for receiving sound waves and modulating phase and amplitude; the control unit is used for controlling the structure and the geometrical shape of the cells in the LAM metasurface; enabling sound waves to reach a decoupling point in the internal structure space of the LAM metasurface under the irradiation of front sound; decoupling modulation of the phase and amplitude of surface reflection sound waves by the cells is realized; and the processor is used for calculating the sound pressure projected to the holographic surface phase position according to the input image, and adjusting the size parameters of the cells in the LAM metasurface through the controller. After the incident sound wave interacts with the LAM metasurface, the incident sound wave is demodulated and re-modulated and is reflected at an angle perpendicular to the LAM subsurface. The LAM metasurface does not apply any angle constraint to incident sound waves; the angle of the reflected wave is always perpendicular to the LAM surface. And the imaging quality of the required phase acoustic hologram after amplitude compensation is met.

The invention discloses a saw blade tooth profile defect visual inspection system based on a deep learning model, and relates to the technical field of saw blade tooth profile defect detection.The saw blade tooth profile defect visual inspection system comprises a light source capable of providing a plurality of different specific wavelengths, and a first visual inspection device shoots a saw blade and generates a digital image; pixel information in the scanning image is subjected to edge detection, texture analysis and morphological operation, and then corresponding characteristic values are extracted; and the second visual detection device is used for receiving the light of different specific wavelengths reflected from the surface of the saw blade in a certain length range, and analyzing and generating reflection spectrum data. The method comprises the following steps: comparing a feature value extracted by a first visual detection device with a set threshold range to preliminarily identify an obvious tooth profile defect area, and taking a comparison result of the feature value and the set threshold as a starting condition for carrying out second accurate detection or not; and the secondary visual detection device performs more accurate detection on the area with the preliminarily detected potential defects, and deep defect features are identified.