1391 results about "Surface reflection" patented technology

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 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.

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.

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 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 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 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 invention provides a plastic packaging barrel online defect detection method and system based on machine vision and deep learning. According to the method, visible light and thermal image data, aligned in time, of the surface of the plastic packaging barrel are collected, the dynamic range of a thermal image is expanded to enhance the identification degree, then highlight interference is compensated through the mapping relation between a thermal image stable area and a visible light reflection area, and surface reflection suppression is achieved; superposing the processed dual-mode data to generate a multi-mode fusion image, dynamically adjusting the temperature reference value of the fusion image based on the thermal conductivity of the material and the environment temperature of the production line, and positioning an abnormal temperature region; and finally, extracting topological contours and temperature diffusion characteristics of the regions, and inputting a deep learning model to judge material structure attributes and spatial positions of the defects so as to finish online detection. According to the method, thermal and visual data are fused to enhance the perception capability on fine structure defects, and the precision and robustness of online detection of the plastic packaging barrel in a complex illumination environment are remarkably improved.

The invention discloses a passive Fourier infrared spectrum gas telemetering control system, which relates to the technical field of telemetering control and comprises an environment sensing module, a dynamic interference correction module, a multi-modal fusion module, a decision display module and an execution feedback module. The environment sensing module synchronously obtains three-dimensional topographic data, a surface reflection polarization state and atmospheric turbulence intensity parameters through a laser radar, a multispectral polarization camera and a quantum meteorological sensor, generates a dynamic topographic-meteorological coupling field model, and corrects spectral signals in real time based on the coupling field model. The terrain reflectivity, the slope angle, the polarization state and the turbulence intensity are comprehensively considered, the accuracy and robustness of spectral signal correction are improved, the AR holographic projection unit is used for converting four-dimensional data into a three-dimensional visual scene in real time, a three-level early warning mechanism is established, and the decision making efficiency and the response speed are improved.

The invention relates to the technical field of exhibition lamps, in particular to an exhibition lamp and an exhibition method, and the method comprises the following steps: inputting preset exhibit database information, extracting exhibit numbers, material types, dominant tone ranges and size information, carrying out point-by-point scanning on exhibit surfaces, collecting reflection spectrum data, converting the reflection spectrum data into CIELAB values, and integrating the extracted information and the collected data. And establishing an exhibit basic information set. The comprehensive exhibit basic information set is established by combining the preset database information and the real-time scanning and acquisition of the surface reflection spectrum or the CIELAB value of the exhibit, so that the subsequent illumination design can be carried out based on the unique optical characteristics of each exhibit, the accuracy and pertinence of personalized illumination are improved, and the material details and color levels can be deeply revealed. Secondly, processing the optical data of the exhibit by using a preset weight set associated with a specific display target, and generating an ideal display illumination parameter including spectral distribution and a brightness value;

The invention provides an apparent defect detection system and method based on CCD image recognition. A specular reflection interference area meeting a preset difference condition is recognized through a first surface reflection image and a second surface reflection image of a target patch element; extracting corresponding orthographic gray scale data from a third surface orthographic image obtained by adopting coaxial light source irradiation based on the specular reflection interference area; according to the brightness distribution gradient of the specular reflection interference area in the first surface reflection image and the second surface reflection image, constructing a texture restoration guide map, and using the texture restoration guide map to carry out texture restoration on the orthographic gray scale data to generate a texture restoration image of the specular reflection interference area; and generating a defect identification reference image for eliminating specular reflection interference based on the texture repair image, and outputting an appearance defect identification result of the target patch element by the defect identification reference image. According to the technical scheme provided by the invention, the defect detection of the patch element can be realized under the interference of mirror reflection.

The invention relates to the technical field of image processing, in particular to an image data processing method and system for digital management of environmental protection equipment, and the method comprises the steps: collecting a real-time image of an aeration area through a waterproof camera disposed above an aeration tank, detecting the definition of the camera regularly, and carrying out the cleaning when the definition is lower than a preset value; a self-adaptive Retinex algorithm is adopted for the real-time image of the aeration area to eliminate water surface reflection interference, noise caused by water turbidity is reduced through a multi-frame weighted average method, and a processed image is obtained; segmenting a bubble region in the image based on a U-Net network and calculating a bubble distribution parameter; comparing the bubble distribution parameter with a bubble distribution threshold value, and generating an aeration rate optimization instruction according to average dissolved oxygen data obtained by a dissolved oxygen sensor; and controlling the air blower based on the aeration rate optimization instruction. The power of the air blower can be better adjusted according to the bubble condition of the aeration tank, so that more energy is saved.

The invention provides a rapid calibration method and system for angle measurement precision of a laser seeker. The method comprises the following steps: emitting a laser beam to a calibration rod array through a laser seeker, and collecting the displacement of a laser spot reflected by the surface of each calibration rod through a position sensitive device; inputting the laser spot displacement into a spot displacement feature extraction network, and generating an angle and displacement time sequence containing a timestamp; identifying abnormal sampling points in the angle and displacement time sequence; and performing geometric reconstruction on the abnormal sampling points by adopting a space geometric constraint optimization algorithm and combining a fixed space included angle constraint relation to obtain angle measurement error calibration parameters of the laser seeker. According to the technical scheme provided by the invention, the high-precision dynamic calibration of the angle measurement error of the laser seeker is realized through the collaborative analysis of the space coordinates of the calibration rod and the displacement of the laser spot in combination with the neural network and geometric constraint optimization.

The invention discloses a bar count visual identification automatic calculation system and method, the system comprises a stereo visual acquisition unit, a dynamic threshold adjustment unit, a geometric feature analysis unit, a data processing module and a man-machine interaction unit, and the method comprises the following steps: S01, image acquisition and preprocessing; s02, adjusting an environment self-adaptive threshold value; s03, bar geometric feature extraction; s04, the number of bars is calculated; s05, outputting a result, displaying the bar count obtained by calculation on an interface of a man-machine interaction unit, and storing a counting result and related data in a database at the same time; the beneficial effects of the invention are that a conventional visual counting system usually only depends on two-dimensional image information, recognition errors are easy to occur under the conditions of bar adhesion, surface reflection and the like, the scheme constructs a stereoscopic vision system through an industrial camera to obtain three-dimensional point cloud data, image textures are enhanced in combination with coding structured light projected by a structured light emitter, and the recognition accuracy is improved. And the spatial position and surface depth information can be obtained.

The invention relates to the technical field of 3D vision measurement, and discloses a 3D binocular line laser weld contour data acquisition method and system. Two core steps of obtaining surface reflection characteristic information of a to-be-scanned area and adjusting output intensity of laser rays projected by a line laser device at different positions of the to-be-scanned area according to the surface reflection characteristic information are introduced, so that the problem that when a high-reflection welding seam is processed by a traditional method, the laser rays cannot be projected by the line laser device is effectively solved; the problem of image overexposure or underexposure caused by dramatic change of illumination characteristics is solved.

The invention discloses a water area dynamic monitoring method and system based on an unmanned aerial vehicle remote sensing technology, and the method comprises the steps: adjusting the shooting angle of each camera according to the flight attitude of an unmanned aerial vehicle, and shooting a target water area photo after stabilization; performing water surface reflection compensation on the target water area picture based on the shooting angle; the compensated photos are sequenced according to the shooting time, and the photos of different shooting angles at the same shooting time are registered and spliced to obtain a panoramic image sequence; dividing the target water area into intervals, extracting an interval image sequence corresponding to each water area interval from the panoramic image sequence, extracting convolution features of each interval image in the interval image sequence, and splicing the convolution features with the shooting time of the panoramic image where the interval image is located and the central position of the corresponding water area interval to obtain a panoramic image sequence; obtaining a multi-dimensional feature vector; and constructing a water quality inversion model based on the multi-dimensional feature vector. The water quality inversion model constructed by the invention can realize dynamic monitoring of a water area and release early warning information more efficiently and accurately.

The invention discloses a self-co-phase detection method for a plane diffraction spliced telescope with built-in vortex light, and belongs to the technical field of optical imaging telescopes. According to the method, an internal light source of the system is used as beacon light, so that a light beam passes through an optical system in a reverse imaging direction and is emitted in a parallel light form, and then enters the optical system again after being reflected by the front surface of a primary mirror to form a detection light beam carrying co-phase error information; and then, the detection light beam and a vortex light beam in the system generate interference on an image plane, and by acquiring and processing interference fringes in real time and extracting attitude information of the primary mirror under the combined action of forward and reverse errors, decoupling and correction of the piston and tilt errors of the spliced mirror surface can be realized, so that the error correction precision and the overall performance of the system are remarkably improved. In addition, two detectors are arranged in the system, interference fringe detection and system imaging can be achieved at the same time, a beacon light source is taken from the interior of the system, and the defect that a traditional method highly depends on external beacon light is overcome.

The diffuse reflection uniform light-emitting car lamp optical system comprises a lamp body, a circuit board, a light source and an aluminized reflection bowl, the light source is arranged on the circuit board, the diffuse reflection car lamp optical system further comprises a diffuse reflection reflecting plate, and the aluminized reflection bowl comprises a first diffusion pattern face arranged corresponding to the light source and a second diffusion pattern face arranged corresponding to the diffuse reflection reflecting plate; light emitted by the light source irradiates the aluminized reflection bowl, is reflected and diffused through the first diffusion pattern surface, irradiates the second diffusion pattern surface for reflection and diffusion, and then irradiates the surface of the diffuse reflection reflector to be reflected. The diffuse reflection uniform light-emitting car lamp optical system is reasonable in design, a good lighting effect is achieved through mutual cooperation of the reflection bowl, the fogging inner cover and the diffuse reflection reflector, and the diffuse reflection uniform light-emitting car lamp optical system is novel in light-emitting form, uniform in light-emitting effect and rich in layering sense.