3282 results about "Mirror plane" patented technology

The invention relates to an endoscope image reflection restoration method based on detection network and filtering fusion, and belongs to the technical field of medical image computer processing. The method aims at improving detection and removal of specular reflection in an endoscope image, a variant of TransUnet is adopted in the detection stage, and U-Net and Transform architectures are combined; the method comprises Atrous spatial pyramid pooling (ASPP), information bottleneck (IB) and a convolutional block attention module (CBAM). The enhancement functions improve the identifiability of specular highlight and solve the problem of weak generalization in endoscope data concentration. In the removal stage, the invention designs an enhanced median filtering module for removing specular reflection. The module first applies Gaussian blur to the repaired region and then calculates color information from the non-reflective region. According to the method, mirror reflection is effectively eliminated from the endoscope image, clearer and more accurate visual information is provided for clinicians, and improvement of diagnosis precision is facilitated.

The invention discloses an intelligent steel pipe surface defect recognition system based on deep learning, and particularly relates to the technical field of pipe surface defect analysis. An annular polarization light source array and a high-frame-rate CMOS sensor are adopted to synchronously collect visible light and near-infrared multi-polarization images; a surface normal is calculated based on Stokes parameters, mirror surface suppression and diffuse reflection enhancement are realized, a defect candidate area is generated by fusing multi-scale Laplacian pyramid residual error and Renyi entropy segmentation threshold positioning, multi-physical quantity registration is completed through white light interference and infrared thermal imaging, a six-channel feature cube is constructed, and a three-dimensional image is obtained. According to the method, space, spectrum and thermal characteristics are jointly extracted in the multi-head attention convolutional neural network, the confidence coefficient is evaluated in combination with Jensen-Shannon divergence, and the polarization angle and the focal length are dynamically adjusted according to the confidence coefficient, so that closed-loop parameter self-optimization is realized, and the micro-scale pitting corrosion and millimeter-scale crack detection precision is remarkably improved.

The invention discloses a multi-mode end point detection system and method for a semiconductor dry process, and relates to the field of gas concentration detection. A gas absorption cell; the reference light path adjusting unit comprises an adjustable attenuator used for adjusting signals; the first photoelectric detector is used for detecting a transmission signal; the second photoelectric detector is used for detecting a reference signal; the lateral scattered light detector is used for detecting a scattered signal of the particulate matters in the gas absorption tank; and the signal processing unit is in signal connection with the first photoelectric detector, the second photoelectric detector and the lateral scattering light detector and is used for performing compensation calculation on the transmission signal based on the reference signal and the scattering signal so as to obtain a corrected gas absorption signal. By adopting the scheme, measurement signal distortion caused by optical mirror surface pollution and particulate matter scattering interference in a semiconductor tail gas optical detection technology is avoided.

The invention belongs to the technical field of optical detection, and particularly relates to a global power wave aberration prediction-based Ritchey-Common detection method and system, and the method comprises the steps: firstly building a three-dimensional optical model through the parameters of a standard spherical mirror, a to-be-detected plane mirror and an interferometer, and combining a preset Ritchey angle and an out-of-focus / astigmatism coefficient, injecting vibration and temperature noise by using Monte Carlo simulation to generate an enhanced training data space; secondly, constructing a phase error adjustment model based on an adversarial network, and decoupling a mapping relation between an adjustment error and wave aberration distortion through a multi-scale attention mechanism and a radial basis function network to realize adaptive correction of sub-aperture phase data; and finally, splicing sub-aperture phases by using a graph neural network and fusing multi-angle full-aperture measurement data to accurately reconstruct the surface shape of the plane mirror to be measured. According to the invention, through confrontation training and dynamic error compensation of physical constraints, the detection efficiency and reliability of the large-aperture optical element are significantly improved.

A mirror surface defect detection system imaging simulation method based on a structured light field comprises the steps that S1, system parameters are calibrated and serve as simulation model input; and S2, deducing a light propagation model of the light field camera, performing light tracing from a sensor, performing parallel calculation on the light field sub-graph array, and solving an incident light vector of the light field camera. And S3, designing a three-dimensional surface shape of a function fitting deformation defect, solving an incident light vector at the defect, and tracing light to obtain a light source point coordinate and illumination intensity. And S4, based on a Lambert diffuse reflection model, introducing a coefficient representing scratch roughness / stain opacity, and establishing a diffuse reflection non-deformation defect gray model. And S5, generating a simulation image and a label thereof. And comparing the simulation image with the real shot image, and evaluating the reliability of the simulation model. And evaluating the operation efficiency of the simulation model. According to the method, the precision and speed of mirror surface defect light field detection imaging simulation are effectively improved, and the method can be applied to parameter optimization, simulation image data set generation and the like before construction of a detection system.

The invention relates to the technical field of assembly production lines, and particularly discloses an assembly production line workpiece defect detection method and system based on machine vision. The method aims at accurately detecting the workpiece defects of the assembly production line, firstly, position information of a lens, a workpiece and a light source of a machine vision device is obtained, a basis is provided for subsequent calculation, the detection accuracy is ensured, and then the incident angle of the mirror surface is determined according to the characteristic information of the lens, influences reflected light and imaging and is a key parameter. Then obtaining imaging influence factors according to workpiece characteristics, measuring interference of workpiece surface characteristics on imaging, providing a basis for optimizing reflectivity, calculating specular reflectance through light source position information, reflecting light reflection conditions, combining the specular reflectance and the reflection conditions to obtain collaborative optimization specular reflectance, more accurately evaluating the influence of reflection on imaging, and finally, determining the influence of reflection on imaging. If the reflectivity is greater than a preset threshold value, correction is carried out, a correction angle is obtained to adjust a lens detection angle, misjudgment caused by mirror reflection is reduced, and the detection precision is improved.

A display device, including a display module, a photodetector, a processor, and an optical structure layer, is provided. The display module is used for displaying an image. The photodetector is electrically connected to the display module and is used for detecting brightness of an ambient light and outputting a sensing signal. The processor is electrically connected to the display module and the photodetector, and is used for receiving the sensing signal and outputting a command signal to the display module according to the sensing signal, so that the display module adjusts brightness of the image according to the command signal. The optical structure layer is disposed on the display module. A glossiness of the optical structure layer is between 4 GU and 35 GU, and a reflectivity of specular component included (SCI) of the optical structure layer is between 3% and 6%.

The invention relates to the technical field of metal material detection, in particular to a titanium alloy bar machining quality detection method and system, and the method specifically comprises the steps: carrying out the superpixel segmentation of the section of a titanium alloy bar, constructing a mirror image edge texture saliency value of a superpixel block based on the proportion of edge points in the superpixel block and the edge gradient, and carrying out the detection of the machining quality of the titanium alloy bar. Constructing the mirror image texture intensity of the titanium alloy bar by combining the gray level distribution concentration characteristics of the titanium alloy bar, and performing image segmentation on the section of the titanium alloy bar; and in each segmented region, based on the edge line fuzzy degree difference and the pixel gray level difference of each super-pixel block and the rest of super-pixel blocks, combining a mirror image edge texture saliency value to construct a segregation evaluation value of each super-pixel block, and based on the segregation evaluation value, carrying out titanium alloy bar segregation quality defect detection. The titanium alloy bar segregation defect identification capability is enhanced, the titanium alloy bar segregation defect detection accuracy under the titanium alloy bar mirror image scene is improved, potential problems can be found earlier, missing detection is avoided, and the defective rate is reduced.

The invention provides a high-reflection plane metal part defect detection method and system based on a composite polarized light source, and a medium. The method comprises the following steps: illuminating a high-reflection plane metal part based on the composite polarized light source, adjusting a light source polarization angle and an LED wave band combination to construct a shooting environment, and collecting an image sequence; calculating a polarization intensity distribution parameter for the image sequence based on the relationship between the polarization intensity and the Stokes parameter to obtain a polarization intensity distribution image; analyzing the polarization intensity distribution image based on a polarized light reflection model, and outputting a specular reflection component and a diffuse reflection component; fitting the specular reflection component and separating the diffuse reflection component to obtain a reflection-removed image; based on an image enhancement algorithm, edge enhancement is carried out on the reflection-removed image to obtain an enhanced image, and based on a defect identification algorithm, the enhanced image is analyzed to obtain defect information; by removing the diffuse reflection component and reconstructing the image, the mirror interference is effectively stripped, and the defect identification precision is improved.

The invention discloses an adaptive optical system non-common-path aberration correction method based on a neural network. The adaptive optical system non-common-path aberration correction method comprises the following steps: constructing a lightweight neural network CP-Net; simulating and generating a perfect point spread function image; generating a deformable mirror control voltage matrix based on the image; taking the voltage matrix as the input of CP-Net for training, and ending the training when the loss function value is smaller than a preset minimum value; the trained CP-Net is connected to an actual control loop, real-time images acquired by a scientific camera are received, and perfect reference voltage is generated and directly used for controlling and changing the mirror surface type of the deformable mirror. According to the method, the deformable mirror control command can be directly generated, aberration does not need to be measured, real-time automatic adjustment can be achieved, compared with a traditional phase diversity method and a stochastic gradient descent algorithm, the operation difficulty can be greatly lowered, the correction time can be greatly shortened, and an operator does not need to manually adjust related parameters in the correction process.

The invention relates to the field of optical system imaging, in particular to an optical system imaging quality prediction model construction method giving consideration to surface shape errors and pose errors, which adopts a Zernike polynomial to perform accurate fitting on mirror surface shape errors caused by bolt pre-tightening force, and adopts a finite element mode to perform simulation on an optical system bolt tightening process. According to the method, Zernike polynomial fitting is taken as a basic parameter, various mirror surface shape errors and assembly pose deviations are fully considered when Zemax is adopted to carry out optical path imaging simulation, and the energy concentration degree is taken as an imaging quality quantitative evaluation index, so that the optical path imaging simulation of the two-mirror optical system is realized. According to the method, an SVR proxy model containing local and global mixed kernel functions is established, sensitivity analysis is performed on mirror surface shape and assembly pose parameters, an assembly data set is obtained through assembly and imaging joint simulation, and the model is trained to obtain an imaging quality prediction model so as to realize rapid and accurate prediction of imaging quality.

The invention relates to the technical field of optical system detection devices, in particular to a large-aperture standard reflector adjusting device, which specifically comprises a bottom plate, an orientation rotating device, a pitching rotating device and a reflector fixing device, and is characterized in that the orientation rotating device is arranged above the bottom plate; the pitching rotating device is arranged above the azimuth rotating device; the reflector fixing device is connected to the pitching rotating device, so that the azimuth rotating device can adjust the azimuth angle of the reflector fixing device, and the pitching rotating device can adjust the pitching angle of the reflector fixing device; wherein the azimuth rotating device and the pitching rotating device have a self-locking function. Therefore, under the condition that the surface type precision of the mirror surface of the standard reflecting mirror is ensured, the standard reflecting mirror can be precisely adjusted at a large angle in the azimuth angle and the pitching angle, and the detection requirement of an optical system is met.

A kaleidoscopic laser beam projector (KLBP) system that employs a single moving structure to project patterns of sweeping laser beams with diverse sweep directions and emission apertures. The system comprises a collimated light source, a spinning mirror deflector (“spindle / flutter mirror”) at the center, and a stationary kaleidoscopic mirror containing multiple facet mirrors arranged in a concave fashion around the spindle mirror. As the spindle mirror rotates, it directs laser beams in a radially whirling movement toward the facet mirrors, which then subdivide these beams into multiple short strokes and redirect them outward in different directions. Various embodiments include configurations with diffractive optical elements (DOEs) for beam splitting, different kaleidoscopic mirror geometries (hexagonal, octagonal, etc.), and innovative flutter mirror mechanisms that create controlled angular variations during rotation. The system enables a “4×1” configuration that replaces traditional “4×4” systems requiring eight motors and multiple moving structures. The KLBP system offers significant advantages including mechanical simplicity, reduced size and weight, improved energy efficiency, enhanced reliability, cost-effectiveness, and modular configurability. The diverse beam incidence angles enable superior illumination of complex three-dimensional objects for applications in machine vision systems, precision metrology, gap and flushness inspection, and robot-assisted assembly of complex structures.

The invention discloses a method for dynamically correcting off-axis aberration of a liquid mirror telescope, which comprises the following steps of: S1, adjusting a secondary mirror body to perform dynamic full-angle circular motion around the center of a primary mirror by using a secondary mirror rotating system, so that the secondary mirror body acquires an incident beam from any direction; s2, acquiring attitude information of the secondary mirror body, and adjusting the secondary mirror body according to the dynamically changeable off-axis angle based on a preset secondary mirror pose adjustment sub-method to compensate for low-order aberration; s3, the light beams of the distorted wavefront compensated by the secondary mirror are adjusted to be emitted in a determined direction in parallel and enter an adjustable beam expanding and shrinking mirror through two groups of plane reflection systems; s4, the light beam with the light spot size adjusted through the adjustable beam expanding and shrinking mirror is reflected to the magnetic liquid deformable mirror through the reflecting mirror; and S5, the magnetic liquid deformable mirror receives the reflected light beam and performs residual aberration correction. According to the method, the observation view field of the liquid mirror telescope can be effectively improved, the imaging quality is improved, and an aberration correction system is endowed with excellent flexibility and wide adaptability.

The invention discloses an optical-mechanical-thermal integration analysis method for a space low-temperature infrared camera, which belongs to the technical field of space optical remote sensing and comprises the following steps of: when a low-temperature infrared optical system is designed, firstly, performing structural modeling on parameters of the infrared low-temperature optical system in a normal-temperature state, and establishing a corresponding structural and thermal control analysis finite element model based on a structural model; a thermal control analysis temperature field is used as structural finite element analysis input, and structural simulation analysis is performed on changes of the mirror surface precision and the mirror surface position of the optical system; processing the precision and position change data into a format which can be identified by low-temperature optical system design software, and importing the data into the optical design software; the optical performance of the low-temperature optical system at low temperature is evaluated through optical design software, the stability of interior orientation elements is evaluated, and the reliability of the low-temperature optical system is improved; the low-temperature optical system provides guidance from normal-temperature adjustment test to low-temperature use; the problem that the performance of a low-temperature infrared optical system is difficult to evaluate and predict under large thermal deformation is solved.

The invention relates to the technical field of quality detection of building materials, in particular to a quality detection method and system for mirror-surface bare concrete. The quality detection method for the mirror-surface bare concrete comprises the following steps: S100, starting three-dimensional detection; s200, carrying out spatial dimension multi-index cooperative detection; s300, time dimension dynamic attenuation analysis is carried out; s400, carrying out environmental adaptability calibration; s500, carrying out digital dimension topological modeling; and S600, carrying out comprehensive quality evaluation. The invention further discloses a system for detecting the quality of the mirror-surface bare concrete. The system comprises a three-dimensional holographic detection module; a dynamic tracking and environment calibration module; a digital modeling engine; a comprehensive evaluation platform; and a data interface module. According to the method, through four-dimensional fusion of space-time-number-environment, multi-dimensional features such as flatness, glossiness, color uniformity and surface and near-surface bubbles are synchronously captured, and quality misjudgment caused by index omission is avoided.

The invention discloses an indoor scene three-dimensional reconstruction method based on deep fusion and confidence modeling, and belongs to the technical field of computer vision. According to the method, composite data frames such as a color image, a depth map, an IMU (Inertial Measurement Unit) and a camera attitude are comprehensively utilized to carry out regional three-dimensional reconstruction on an indoor scene: firstly, the scene is divided into a smooth region (such as a wall, a ground, a ceiling, a glass plane, a mirror surface, a blackboard and other planes) and a complex curved surface region; aiming at the smooth area, adopting geometric prior guide plane fitting provided by a visual large model, and combining sensor attitude information to quickly reconstruct a regular plane model; for a complex curved surface area, a multi-frame point cloud fusion strategy is adopted to accumulate different view angle information, and a deep residual error refining network is utilized to recover curved surface details, so that a high-precision curved surface model is obtained. According to the method, the three-dimensional structure of the indoor scene can be efficiently reconstructed, the global framework of the smooth area is reserved, and the details of the surface of a complex object are depicted in detail.

The invention relates to the technical field of machine vision and optical detection, in particular to a tea color automatic evaluation method and system based on machine vision. The method comprises the following steps: constructing a stable and repeatable optical measurement environment and calculating radiation baseline parameters; performing multi-band polarization sequence imaging on the tea sample to obtain original data with spectrum and structural characteristics; separating mirror surface and diffuse reflection components on the surfaces of the tea leaves, and performing spectrum consistency correction by combining a radiation baseline; performing multiband spectrum reconstruction and normalization processing on the basis of the corrected diffuse reflection image, mapping to a CIE Lab color space, extracting pixel-level brightness, chromaticity and color distribution statistical indexes, and generating a color feature vector in combination with spatial weighting matrix optimization; a final score is calculated by constructing a quantitative evaluation and grade judgment model and integrating perception color separation, drying calibration color separation and a penalty term, and a grade result is output. According to the method, objective, accurate and automatic evaluation of the color of the tea leaves is realized.

The embodiment of the invention discloses a point cloud denoising method, and the method comprises the steps: obtaining the to-be-denoised point cloud data which is the point cloud data collected in a designated region based on a preset collection track; on the basis of the acquisition track, filtering point cloud data outside the specified area from the to-be-denoised point cloud data; detecting a mirror surface range in the specified area; and in the filtered point cloud data, the point cloud data collected from the interior of the mirror surface range is deleted to obtain the denoised point cloud data, so that the filtering effect of the point cloud data collected in the specified area can be improved.

The invention relates to the technical field of mirror surface detection equipment. The invention discloses bathroom mirror surface flatness detection equipment and a use method thereof.The bathroom mirror surface flatness detection equipment comprises a test board, a placement table used for placing a bathroom mirror is arranged on the test board, a driving assembly is arranged on one side of the placement table, and an auxiliary moving assembly is arranged on the driving assembly; the auxiliary moving assembly is provided with a plurality of detection devices used for detection, the detection devices are arranged at equal intervals, the side end of each detection device is provided with a starting assembly, the side end of each starting assembly is provided with a marking assembly, and each detection device comprises a reaction assembly and a matching assembly. According to the invention, the auxiliary moving assembly and the detection device work to automatically carry out synchronous detection on the concave and convex surfaces of the bathroom mirror surface and mark the flaw part, so that the detection efficiency and the practicability are greatly improved.

The invention relates to a sight angle rate extraction method based on depth target tracking, and relates to the field of navigation control and computer vision. Comprising the steps of deploying a variable-focus optical camera on an unmanned aerial vehicle, and setting a normal of the center of a mirror surface of the camera to be inclined at a certain angle with a horizontal plane for acquiring complete information of a target; calibrating the target in the camera based on an optical parameter calibration method, and obtaining a field angle of the target relative to the center of the camera; deploying a target tracking algorithm on the unmanned aerial vehicle, and identifying a target position based on the target tracking algorithm; obtaining a horizontal deflection angle and a pitching deflection angle of the target relative to the center of the camera by combining a target position identified by a target tracking algorithm based on the field angle; and estimating the line-of-sight angular rate through Kalman filtering based on the obtained horizontal deflection angle, the obtained pitching deflection angle and the flight parameters of the unmanned aerial vehicle. Through combination of parameter calibration of the optical camera and a target tracking algorithm based on deep learning, the horizontal deflection angle and the pitching deflection angle of the target can be accurately obtained.

The invention relates to the technical field of optics and control, and discloses a light beam pointing stabilization method and system based on simulation environment driven reinforcement learning, and the method comprises the steps: dividing an integrated light path into a plurality of sub-light path links according to the serial connection relation of upper and lower levels in the integrated light path; the mirror surface deflection angle of the fast reflecting mirror group and light beam pointing drift data before and after swinging are recorded, and a sample data set is formed; constructing a simulation environment model based on a convolutional neural network based on the sample data set; the simulation environment model is used as a virtual interaction environment, a light beam pointing correction agent is constructed, and a reinforcement learning framework is used for training; the light beam pointing correction intelligent agent is used in the actual light path of the real environment, reinforcement learning training continues to be carried out through the actual light path of the real environment, and after training is completed, the light beam pointing correction intelligent agent is used for controlling the fast reflecting mirror set of the light beam pointing adjustment device of the real environment; according to the invention, the problem of light beam drift of a complex series coupling light path system in a multi-type interference environment can be solved.

The invention relates to the field of laser micro-nano machining, in particular to an ultrafast laser high-stability welding method and device for heterogeneous materials, effectively solves the problem of welding defects caused by unstable metal surfaces during ultrafast laser welding of large-diameter transparent / metal heterogeneous materials, effectively improves the welding strength and stability, and improves the welding quality. And the mirror surface and non-mirror surface metal welding quality unification is realized. The method specifically comprises the steps that the light emitting mode of ultrafast laser is adjusted, monopulse output is converted into Burst pulse string output, the ultrafast laser in the Burst output mode is used for conducting polishing pretreatment on the surface of the metal material, stable control over the surface quality of the mirror surface and the surface quality of the non-mirror surface metal can be achieved, and the surface roughness after polishing can be controlled to be smaller than lambda / 4; the transparent material and the polished metal material are welded through ultrafast laser, stable control over the welding strength of the heterogeneous material can be achieved, and the welding strength of the mirror-surface metal material is close to that of the non-mirror-surface metal material.

An illumination optic (11) for projection lithography has a transmission facet mirror (6), an illumination specification facet mirror (7), and a monitoring device (28). The latter has at least one spatially resolving monitoring sensor (29) and a satellite facet (30), which belongs to the transmission facet mirror (6) and is each assigned to exactly one monitoring transmission facet (21). The satellite facet (30) is oriented such that monitoring light (3) from a monitoring light source (2) is guided via the satellite facet (30) and a monitoring illumination control facet (25), which is assigned to the monitoring transmission facet (219) via an illumination channel (27), along a monitoring light channel (31) to the monitoring sensor (29). This results in an illumination optic in which a tilting of illumination control facets of an illumination control facet mirror can be effectively monitored.

The invention discloses a primary and secondary mirror combined detection system and method for a beam shrinking system, and belongs to the technical field of optical detection.The method comprises the steps that a first micro-spherical mirror and a second micro-spherical mirror are arranged, reflection light spots are captured through an interferometer, the position offset is calculated, and a first control instruction for adjusting the pose of a secondary mirror is generated; a dual-band light source is integrated in a detection light path, wavefront data and alignment monitoring data are collected, and temperature drift is corrected to obtain effective combined wavefront; an error separation model is constructed based on the primary mirror compensator parameter and the Zernike aberration coefficient, and a primary mirror surface shape error component and a secondary mirror offset error component are decoupled and separated by using a preset aberration coupling coefficient; feeding the error component back to a polishing process and a displacement table for closed-loop iterative correction until the RMS value and the PV value of the effective combined wavefront meet a preset imaging quality index; through precise positioning, error correction and decoupling separation, the precision and efficiency of primary and secondary mirror combination detection are improved, and targeted correction is realized.

The invention relates to the field of mechanical engineering, in particular to an assembly error-based optical system imaging quality prediction method, which comprises the following steps of: firstly, constructing an accurate optical system finite element model, simulating a bolt tightening process, obtaining mirror surface deformation under the action of assembly stress, fitting a mirror surface shape by utilizing a Zernike polynomial, taking the mirror surface shape as an intermediate medium, and predicting the imaging quality of an optical system. The Zemax is adopted to simulate the imaging of the optical system under the conditions of mirror surface deformation and assembly poses, and the influence rule of various assembly errors on the imaging quality of the optical system is explored. Thirdly, an assembly data set is constructed through an integrated simulation method, an MLP-XGBoost combined neural network agent model is established, model training is carried out, and compared with a single MLP model, a single XGBoost model and a traditional regression model, the method has higher superiority and reliability in the prediction precision aspect. And finally, a stochastic gradient descent method is adopted to optimize the pre-tightening force under different primary and secondary mirror assembly pose conditions, the energy concentration ratio is averagely improved by 11.34% compared with the energy concentration ratio before optimization, and the assembly and adjustment efficiency and precision of the double-mirror optical system are improved.

The invention relates to the field of three-dimensional vision measurement, in particular to an aluminum alloy CNC product defect detection method and system based on structured light scanning. The aluminum alloy CNC product defect detection system based on structured light scanning comprises an image acquisition and analysis module, a self-adaptive illumination control module, a point cloud reconstruction module, a defect detection module and a report generation module. According to the method, through texture direction perception and matrix type light source dynamic angle modulation, and in combination with a light intensity-wavelength self-adaptive scheme of saturated pixel grading, mirror surface glare of the aluminum alloy high-reflection surface is greatly reduced; in cooperation with multi-exposure gray scale weighted fusion, a stripe image which is uniform in contrast and free of overexposure can be obtained in single scanning; in the same scanning time, compared with a fixed illumination scheme, the point cloud integrity rate can be improved, and a more reliable three-dimensional data basis is provided for subsequent defect detection.

The invention discloses a control method and system for enhancing repetition precision of a laser galvanometer, and the method comprises the steps: collecting laser power fluctuation and mirror surface temperature sequence data, obtaining a heat effect state vector through preprocessing, carrying out the noise interference updating of the heat effect state vector, inputting the heat effect state vector into a neural network model, and obtaining a preliminary thermal deformation predicted value; calculating an angle compensation parameter in combination with a preset compensation matrix to obtain a preliminary compensation signal; posterior state estimation correction is carried out, control parameters are adjusted, and enhanced compensation signals are obtained; then generating an instruction input sequence and carrying out iterative optimization to obtain an optimized angle compensation parameter; fusing position feedback to obtain a stable output track; and calculating the deviation between the angle compensation parameter and the real-time trajectory data, optimizing a heat effect state vector to obtain an optimized heat effect state vector, and recalculating the angle compensation parameter to obtain a final angle compensation parameter. According to the method, the track precision and stability of the laser galvanometer system under the complex heat effect can be remarkably improved.

A micron-sized speckle preparation method for quasi-in-situ OIM-DIC mesoscopic strain field analysis comprises the following steps: (1) polishing the surface of a sample to be detected to obtain a bright and scratch-free mirror surface; (2) preparing Si powder turbid liquid; (3) dipping speckles of a sample to be detected in the Si powder turbid liquid to obtain micron-sized speckles; and (4) observing and shooting speckle morphology, and if Si particles are uniformly distributed and dispersed, applying the Si particles to quasi-in-situ OIM-DIC mesoscopic strain field analysis. The method is simple, convenient and rapid, low in operation and construction cost, high in practicability, good in particle dispersity, high in precision, more suitable for calculation of a quasi-in-situ OIM-DIC mesoscopic strain field, controllable in preparation process, low in cost and free of damage to the surface of a sample, the definition and stability of speckle characteristics are remarkably improved, DIC mesoscopic micron-scale operation under a quasi-in-situ OIM mechanical test can be effectively achieved, and the method is suitable for large-scale industrial production. And the grain and mesoscopic strain field information is successfully coupled.