247 results about "Digital image correlation" patented technology

The invention relates to a deformation online measurement and control method for multi-robot collaborative assembly. The method comprises the steps that multi-view surface images of workpieces in the assembly process are collected in real time through distributed robots and cameras arranged at the tail ends of the distributed robots; each view angle surface image is input into a deep learning model trained based on a digital image related technology, the optimal pixel displacement corresponding to each view angle surface image is output, and the optimal pixel displacement corresponding to each view angle surface image is converted into a spatial displacement label; the deep learning model takes an encoder-decoder as a trunk network; fusing the spatial displacement labels corresponding to the view angle surface images to obtain a fused displacement field; based on the fusion displacement field and the nominal path planning point, the tail end pose of the distributed robot is determined; the assembly error is calculated based on the reference target positioning and the tail end pose, and the PID controller adjusts the joint space of the distributed robot based on the assembly error. According to the method, the calculation overhead is remarkably reduced, and the measurement precision and robustness are improved.

The invention relates to the technical field of digital image correlation DIC measurement, in particular to a DIC displacement field dynamic correction method and system based on a lightweight convolutional network, and the method comprises the steps: 1, collecting a structure surface image sequence, and carrying out the preprocessing; 2, calculating an initial displacement field of the preprocessed image sequence through a traditional DIC algorithm, extracting key feature information, and taking the key feature information as input data for dynamic correction; 3, constructing a lightweight convolutional neural network model, transmitting the extracted input data to the lightweight convolutional neural network model for recognition, designing a mixed loss function for training, and learning a mapping relation between an initial displacement field and a real displacement field; and 4, correcting the initial displacement field through the trained lightweight convolutional neural network model, and directly outputting corrected high-precision displacement field data. By using the function fitting capability of the neural network, high-precision displacement field correction is realized under limited computing resources, and the measurement precision is improved.

The invention discloses a thermal shock failure prediction and laser repair device for a thermal barrier coating and an application method. The device comprises a multi-physics field coupling simulation analysis module, a thermal shock experiment loading module, an online damage monitoring and failure diagnosis module, a robot laser repair execution module and a central control and data processing core unit. A thermal-mechanical-chemical coupling model is established to predict a coating failure behavior, a high-frequency induction heating and gas quenching system is adopted to simulate an extreme thermal shock environment, a multi-band thermal infrared imager, an ultrasonic probe and a digital image related system are integrated to monitor damage evolution in real time, and in-situ repair of a damaged area is realized based on a six-degree-of-freedom industrial robot. According to the method, the whole-process closed-loop control from failure prediction to repair regeneration is realized, the problems of single function and lack of multi-field coupling analysis and real-time repair capability in the prior art are solved, and the service reliability evaluation precision and the remanufacturing efficiency of the thermal barrier coating are remarkably improved.

The invention discloses a method and a system for rapidly measuring cable force of a stay cable based on a digital image correlation method. The method comprises the following steps: acquiring video data of the stay cable; a line segment measurement calibration method is adopted, stay cable texture points serve as feature points, and a feature point selection mechanism is established; establishing a pixel-physical space coordinate mapping model based on a redundant observation method; model parameters are calculated through a collaborative calibration method; performing displacement measurement based on a digital image correlation method; establishing a double-layer feature extraction mechanism to complete local and global feature extraction; weight distribution of the local features and the global features is dynamically adjusted through a weight adaptive fusion strategy; and finally, establishing a double-layer tracking and failure recovery mechanism to complete hierarchical collaboration of coarse-grained global tracking and fine-grained local tracking. And carrying out fast Fourier transform on the dynamic displacement measurement result, and calculating to obtain the cable force. And reliable technical support is provided for non-contact accurate calculation and measurement of the cable force.

An exemplary system and method that employ inverse-problem analysis that can determine spatially-varying mechanical parameters in a spatially-varying field of a heterogeneous material. Mathematically, the computation simultaneously poses the inversion program and an image registration problem in a continuum limit function space setting to derive a discretization dimension-independent algorithm for the robust inference of heterogeneous material properties. The algorithm can operate using two or more images of a speckled pattern or other non-uniform patterns applied to, or observable of, the surface of the material in a first state and a second state different from the first state. The difference can be used to assess, via a Newtonian-based operator, the infinite-dimensional spatial fields as state variables that are regularized via a regularization model to constrain the inherent ill-posed nature of inverse problems.

The invention belongs to the field of material mechanical property testing and strain measurement, and particularly relates to a local strain measurement method and system based on a four-point bending and digital image correlation (DIC) technology, and the method specifically comprises the following steps: cutting to prepare a sample, carrying out surface electrolytic polishing, preparing speckles on the surface of the sample to be tested, and carrying out a four-point bending experiment; speckle images of the lower surface of the sample are collected, displacement correction is conducted in combination with bending deflection calculation, the bending load and the strain of the upper surface of the sample are obtained in real time, the stress-strain relation and local strain distribution of the lower surface of the sample are obtained through calculation, and finally deformation and failure mechanism analysis is conducted in combination with surface deformation and crack morphology. The method provided by the invention combines four-point bending and DIC plane strain measurement technologies, can realize stretching, compression and dynamic fatigue loading on the surface of the sample, is suitable for performance test and failure analysis of tension, compression and fatigue deformation of brittle metal materials such as intermetallic compounds and amorphous materials, and has the characteristics of convenience, rapidness and low cost.

The invention discloses a cylindrical roller trajectory tracking method and device, and the cylindrical roller trajectory tracking method comprises the following steps: obtaining an actual measurement displacement sequence of a key point on the end surface of a roller under a global coordinate system based on a multi-reference matching digital image correlation method; drawing a key point displacement curve about key points and time according to the actually measured displacement sequence; judging the motion state of a roller according to the shape characteristics of the key point displacement curve, dividing a smooth part in the key point displacement curve into a rolling area, and dividing a part with jumping or sharp points into a sliding area; calculating the actual revolution angular velocity and the actual rotation angular velocity of the roller based on the actually measured displacement sequence corresponding to the sliding area; according to the method and the device, the image matching precision can be improved, meanwhile, the rolling and sliding components of the roller are accurately distinguished, the precision of the track of the cylindrical roller is improved, and high-precision and visual experimental data are provided for existing dynamics and tribology models.

The invention relates to a slope monitoring point arrangement method based on sparse spatial correlation and displacement sensitivity. The method comprises the following steps: firstly, carrying out geological survey on a site slope to obtain variability parameters of a slope soil body; then, a slope finite element model is constructed on the basis of slope geometric parameters and the variability parameters, and the displacement states of the slope under different parameter conditions are determined on the basis of the slope finite element model; grading the slope sensitive area based on the displacement state; obtaining displacement data based on the grade of the slope sensitive area, and determining a displacement correlation coefficient and a spatial correlation coefficient based on the displacement data by adopting a Pearson's correlation coefficient and a digital image correlation technology; and finally, determining a slope high-correlation area based on the displacement correlation coefficient and the spatial correlation coefficient, and setting a monitoring point position. The scientificity and accuracy of slope monitoring point arrangement are improved, and the method has certain significance for predicting and preventing slope disasters.

The invention relates to the technical field of structural design and optimization, and particularly discloses a structural error tolerance model construction method for compartment connection positioning, which comprises the following steps of: obtaining real point cloud data of a bolt connection pair through three-dimensional laser scanning, and realizing parameterized digital geometric modeling in combination with a deep neural network; material attributes are given, and self-adaptive grid division is carried out; generating a dynamic load sequence based on a vehicle driving condition, applying the dynamic load sequence to the model, and extracting full-field displacement vector data by using a digital image correlation technology; further identifying a micro-slip area of the contact interface, and calculating an energy dissipation index of the micro-slip area; a quantitative mapping relation between energy dissipation and fatigue life is established through experimental calibration, key design parameters are iteratively optimized by adopting a pattern search method with the target life as a constraint, and finally a connection structure scheme meeting the durability requirement is output.

The invention discloses a fragile material crack detection and damage evaluation method based on box dimension. Change information of a material surface displacement field is calculated by adopting a DIC technology (a digital image correlation technology), a main strain graph is obtained, then the box dimension of the material surface main strain field is calculated by combining a fractal theory, and the damage degree of the material is quantified based on change development of the box dimension. According to the invention, the development process of the cracks of the material test piece from no to penetrating through the test piece can be observed, the crack growth path can be obtained, the crack development can be quantified through the specific box dimension, the damage degree of the structure can be evaluated, and the early warning of the large crack propagation behavior is realized. The method has important practical engineering significance for health detection and risk assessment of fragile material structures such as steel fiber reinforced concrete.

The invention discloses a wide-temperature-range three-dimensional pressure field measurement method in an extreme wind tunnel environment, and the method achieves the high-precision reconstruction of a three-dimensional pressure field in a whole temperature range from low temperature to high temperature through the fusion of a digital image correlation (DIC) technology and a multi-mode sensing technology, specifically, in a low-temperature environment, pressure-sensitive paint and temperature-sensitive paint are used for joint calibration, and the measurement precision of a wide-temperature-range three-dimensional pressure field is improved. A laser light source and double cameras are synchronously triggered through a binocular vision system, fluorescence lifetime signals are captured, temperature interference is eliminated through a double-gating gain function ratio, a three-dimensional shape is reconstructed in combination with a DIC technology, and non-contact pixel-level pressure field mapping is achieved. In a high-temperature environment, pressure measuring point layout is optimized through CFD simulation, discrete pressure data are acquired by adopting a high-temperature-resistant pressure sensor array, sensor space coordinates are acquired in combination with a binocular DIC system, a two-dimensional pressure field is reconstructed by utilizing a Kriging interpolation algorithm, and a three-dimensional pressure field is obtained through pixel-level mapping and three-dimensional point cloud fusion. And a high-resolution three-dimensional pressure field in a high-temperature environment is generated.

The invention provides a method for solving transgranular or intergranular failure of a rock material numerical model based on two-dimensional digital image correlation, and belongs to the field of rock mechanics and geotechnical engineering. The method comprises the following steps: firstly, collecting surface structure characteristics of a rock material, and acquiring geometric characteristics of the surface of the rock material through a scanning technology; the microscopic structure of the rock material is modeled, a Voronoi division method is adopted to divide a numerical model, and in combination with surface feature data, geometric features of the rock material are precisely restored, model parameters are adjusted, and guarantee is provided for subsequent loading operation. And secondly, carrying out loading operation on the established model, simulating deformation and damage processes of the rock under different stress conditions, and monitoring a displacement field on the surface of the model in the loading process to obtain high-precision displacement data. And finally, judging the type of the destruction mode according to the displacement data. According to the method, the type of the rock numerical simulation microscopic crack can be judged, the method is convenient, and the result is accurate.

The invention provides a ground-air combined road slope collapse measurement system and method, and relates to the field of road slope inspection. According to the system, all-weather non-contact acquisition of millimeter-level displacement data of side slope key points is realized through a scientific-level CMOS camera of the ground detection module and a digital image correlation algorithm, and a high and steep side slope is covered; the aerial detection module carries a synthetic aperture radar and a multispectral sensor through an unmanned aerial vehicle to obtain a slope overall three-dimensional deformation field and soil humidity data. Carrying out high-precision space-time registration on the data layer by adopting a dual-function mark point and a least square method; calibrating aerial deformation data on the feature layer through ground displacement data to realize association of macroscopic and microscopic features; and constructing an improved U-Net network and a hybrid prediction model in the model layer to realize accurate tracking of the crack and prediction of the collapse probability. Visual display is carried out through a digital twin platform, and graded early warning linked with a traffic management system is triggered. According to the invention, the limitation of a single detection mode is overcome, and accurate perception, intelligent prediction and dynamic response of road slope safety are realized.

The invention belongs to the technical field of tailing strain field evolution prediction, and discloses a full-tailing cemented filling body strain field evolution and crack prediction method, which comprises the following steps: preparing a full-tailing cemented filling body CPB sample, and carrying out an expansion degree test in the preparation process of the CPB sample; evaluating the uniaxial compressive strength of the CPB sample, and monitoring the surface change of the sample in the testing process through a digital image related acquisition technology; establishing a computer visual identification model based on an HSV color mode, and analyzing the area proportion and distribution condition of strain regions of different degrees to realize comprehensive analysis of the image; and determining an early warning signal of crack prediction according to an analysis result of the change condition of the strain field. According to the strain field evolution and crack prediction method for the full-tailing cemented filling body, quantitative analysis of strain evolution of the filling body is achieved, prediction and early warning are provided for the damage risk of the filling body, and the method has important significance for ensuring the safety and efficiency of mine operation.

The invention belongs to the technical field of three-dimensional vision measurement, and relates to a deformation measurement method and system of a composite vision measurement unit. The internal and external parameters of the binocular measurement unit are obtained according to the image of the thrust vectoring nozzle target area calibration plate; obtaining coordinates of all binocular measurement units in the same reference coordinate system according to the internal and external parameters and the images of the thrust vectoring nozzles with the first coded mark points, and obtaining coordinates of all binocular measurement units in a unified coordinate system; and acquiring full-field deformation of all target areas of the thrust vectoring nozzle according to the speckle images of the target areas of the thrust vectoring nozzle in the working state and the coordinates of the unified coordinate system of all binocular measurement units. According to the invention, a digital image correlation method and a close-range photogrammetry technology are utilized to realize coordinate system unification and full-field deformation measurement. Compared with a traditional method, the measurement times and data processing steps are reduced, and the measurement efficiency is improved.

The application discloses a kind of based on transparent soil and pile-soil interface micro evolution measurement method of multi-source sensing, it is related to geotechnical engineering test field.The present application includes the following steps: constructing transparent soil model, pile body pre-embedded sensor arrangement, multi-source sensor calibration and parameter optimization, load application and multi-source data acquisition, improved DIC algorithm's pile-soil interface micro displacement calculation, pile-soil interface pore and particle density calculation, multi-source sensing data's heterogeneous fusion, pile-soil interface micro evolution characteristic quantitative inversion and visualization, test end and data verification.The present application simulates real soil environment by constructing transparent soil model, in combination with image recognition, digital image correlation, fiber-optic sensing and resistance sensor and other multi-source sensing technology, the micro deformation, stress distribution and failure evolution process of pile-soil interface in loading process are monitored and analyzed in real time with high precision, realize the high-precision, full-process, visual measurement of pile-soil interface micro evolution, improve measurement precision.

The invention discloses a multifunctional asphalt mixture rut test method which is implemented by using a device integrating loading and measurement, test piece supporting and temperature control drainage, environment simulation and optical measurement and a central control and data acquisition system. A test piece is arranged in the test piece groove, temperature control is realized through circulating a heat-conducting medium in the temperature-conducting cavity, different gradients are formed through the hoisting mechanism and the angle adjusting assembly, the test wheel is driven to perform one-way circulating loading along a closed track and snub at a preset moment, and rolling and sliding friction forces are synchronously collected; in the test process, rainfall is simulated by adopting the watering assembly, incoming water is recycled by the drainage tank, speckle images are acquired by the high-frequency industrial camera, and surface full-field displacement and strain are obtained through digital image correlation analysis. Through time registration and fusion of temperature, gradient, wheel speed, rainfall and friction-deformation data, rut deformation, skid resistance and apparent structure evolution laws of the asphalt mixture under multi-climate and multi-gradient conditions are obtained.

Methods, systems, and non-transitory computer readable storage media are disclosed for generating neural network based perceptual artifact segmentations in synthetic digital image content. The disclosed system utilizing neural networks to detect perceptual artifacts in digital images in connection with generating or modifying digital images. The disclosed system determines a digital image including one or more synthetically modified portions. The disclosed system utilizes an artifact segmentation machine-learning model to detect perceptual artifacts in the synthetically modified portion(s). The artifact segmentation machine-learning model is trained to detect perceptual artifacts based on labeled artifact regions of synthetic training digital images. Additionally, the disclosed system utilizes the artifact segmentation machine-learning model in an iterative inpainting process. The disclosed system utilizes one or more digital image inpainting models to inpaint in a digital image. The disclosed system utilizes the artifact segmentation machine-learning model detect perceptual artifacts in the inpainted portions for additional inpainting iterations.

A system and method for analyzing mechanical properties of biological tissues combines light-sheet fluorescence microscopy with mechanical perturbation capabilities. The system integrates a MEMS-based compression device, high-speed light-sheet scanner, and digital image correlation analysis to characterize viscoelastic properties of three-dimensional cellular structures. The system enables quantification of spatially-resolved mechanical characteristics and cellular responses through volumetric strain analysis, correlating mechanical properties with fluorescence-based cellular markers. Implementation with maternal-fetal interface models demonstrates capabilities in analyzing tissue mechanics during cellular invasion processes. The system provides applications in studying mechanical interactions in biological processes including embryonic development, cancer metastasis, and wound healing. The disclosed methodology enables unprecedented analysis of mechanical property dynamics at cellular interfaces in three-dimensional tissue environments.

The invention provides a large-view-field high-precision monitoring method and system, and relates to the technical field of real-time monitoring. The detection method combines a machine vision technology and a DIC technology based on deep learning to optimize a monitoring process, can perform high-precision deformation monitoring on multiple points of a large view field, and is suitable for deformation monitoring of reservoir dam abutment rock mass; before detection, a convolutional neural network is used to carry out defogging operation and intelligent analysis on a surface image of a to-be-detected area, a key target area is automatically identified, and errors caused by manual intervention are effectively avoided; after the target area is determined, displacement field distribution of the target area is calculated by adopting a digital image correlation algorithm based on deep learning, and deformation measurement with sub-pixel-level precision is realized; through fusion of deep learning and a traditional image processing technology, the influence of manual parameter setting is reduced, the problem of decorrelation during matching is solved, and the precision and reliability of displacement calculation are effectively improved.

A data uploader uploads a first plurality of data values associated with a transaction. A document uploader uploads digital images of a plurality of documents associated with the transaction, wherein a second plurality of data values are embedded in the documents. The digital images are stripped of numerical (or other) data values before being transmitted to a first machine learning engine to identify documents associated with the digital images. A second machine learning engine identifies categories of numerical data values (and other data values) that are included in the second plurality of data values and that are embedded in the documents. The first and second plurality of data values can be compared for accuracy and corrected. The first and second machine learning engine are sent bifurcated feedback regarding the respective identification performed by each to improve future accuracy.

The invention discloses a self-adaptive illumination adjustment image measurement method, and belongs to the technical field of image measurement. According to the method, adaptive adjustment is carried out on hardware and a related algorithm simultaneously according to environment illumination changes, the exposure amount of an image is changed by adjusting the exposure time of a camera on the hardware, and exposure adjustment is used for ensuring that the gray level distribution of an image sequence obtained by the camera in an interested area is consistent with that of a reference image as much as possible in the measurement process. Exposure adjustment of a camera is global adjustment for an image, and overexposure or underexposure pixel points still possibly appear in a local area of the image. Therefore, an illumination robust digital image correlation algorithm is provided, the gray level distribution of the sub-regions is adjusted in real time during correlation calculation, the registration precision of the sub-regions is improved by removing saturated pixels in the sub-regions, the sizes of the sub-regions are adaptively adjusted according to illumination changes, it is ensured that the sub-regions contain enough and rich gray level information, and the registration precision of the sub-regions is improved. And the robustness of a related algorithm in suppressing illumination interference is improved.

The invention relates to an electric arc additive mixed end plate connecting device and a performance prediction method, and the method comprises the steps: manufacturing a WAAM end plate at the end part of a conventional steel pipe through multi-axis metal 3D printing, and forming a mixed connecting piece; the two mixed connecting pieces are in butt joint through high-strength bolts to form the mixed end plate connecting device; geometric characteristic parameters of the mixed end plate connecting device are obtained by adopting a three-dimensional scanning technology, and the mechanical response of the mixed end plate connecting device is measured by combining a four-point bending test with a digital image correlation technology; and on the basis of the geometrical characteristic parameters and the mechanical response data, the yield bearing capacity is predicted through a correction yield line analysis method, and the ultimate bearing capacity is predicted by adopting an equivalent beam model considering the strain hardening effect. The device and the method have the beneficial effects that geometric characteristic measurement, interface connection characteristic and yield performance test, bearing prediction evaluation and application design of the mixed end plate connecting device combining the electric arc additive manufacturing stainless steel, low-carbon steel and high-strength steel end plates with the conventional steel pipe can be effectively realized.

The invention provides an ammonia hydrogen energy structure material constant strain rate and constant load stress corrosion synchronous monitoring platform based on acoustic emission and an implementation method thereof. Comprising a gas supply and pressurization system, a constant strain rate and constant load stress corrosion synchronous test system, a gas leakage safety control system, an acoustic emission and digital image correlation (DIC) technology online monitoring analysis system, a temperature control system and a computer integrated analysis system. In-situ dynamic analysis of stress corrosion crack propagation is realized in combination with a DIC technology; the temperature control system realizes accurate temperature control on the corrosion test reaction kettle through an independent temperature control module; the computer integrated analysis system processes multi-source data, and establishes dynamic mapping between acoustic emission characteristic parameters and corrosion crack growth rate. The platform solves the problems of off-line monitoring, single loading mode and the like of a traditional corrosion test, captures a corrosion-induced crack propagation process in real time, improves test efficiency and analysis comprehensiveness, and provides powerful support for research on corrosion behaviors of ammonia hydrogen energy structural materials.

The invention relates to the technical field of retina analysis, and discloses a fundus optical coherence tomography image feature point automatic positioning method, which comprises the following steps: acquiring optical coherence tomography images of a fundus disease patient at different disease course stages, constructing an image database containing a training set and a verification set, and determining the feature points of the fundus optical coherence tomography image on the basis of the image database. And carrying out feature layer segmentation on the image by adopting a U-Net convolutional neural network. And determining a blood vessel shadow position in the fundus optical coherence tomography image and acquiring a boundary of the blood vessel shadow position based on the pigment epithelium gray scale curve. And determining the position of a seed point and the size of a subarea by combining an important layer boundary and a vessel shadow boundary, and assisting digital image correlation to realize retina full-field deformation measurement. According to the method, through deep fusion of deep learning and an image processing technology, the problem of automatic selection of the seed points in the fundus OCT image is solved, the efficiency, precision and reliability of retinal deformation measurement are remarkably improved, and a powerful technical tool is provided for mechanism research and clinical diagnosis and treatment of fundus diseases.

To provide a method of acquiring a strain distribution generated in an object to be measured by the use of a digital image correlation method (DIC), wherein a pattern that the SIC can recognize can be formed on the object to be measured safely no matter how unexperienced a worker is.SOLUTION: A strain distribution acquisition method includes: a first process S1 of forming a pattern 2 that a digital image correlation method (DIC) can recognize on an object 1 to be measured; a second process S2 of acquiring a reference image of the object 1 to be measured, the reference image being an image of the pattern 2 before a load 7 is placed on the object 1 to be measured; a third process S3 of acquiring an image of the pattern 2 of the object 1 to be measured after the load is placed on the object 1 to be measured; and a fourth process S4 of acquiring a strain distribution of the object 1 to be measured from the reference image and the image acquired in the third process S3. In the first process S1, the pattern 2 formed on a master pattern member 3 is transferred to the object 1 to be measured so as to form the pattern 2 on the object 1 to be measured.SELECTED DRAWING: Figure 1

The invention discloses a non-contact measurement system and method for full-field deformation of a fuselage in an airplane crash test, and belongs to the technical field of airplane structure strength testing, and the method comprises the steps: making a high-quality speckle pattern on the surface of the fuselage, and laying cooperation mark points; a binocular camera flexible self-calibration method is used for completing calibration of the stereo measurement system; unification of global coordinates of multiple systems is assisted through unmanned aerial vehicle photogrammetry; a synchronous controller is adopted to trigger multiple sets of systems to synchronously collect images in the falling and collision process; obtaining the motion trail and speed of the key measuring point based on a mark point positioning tracking and stereoscopic vision principle; acquiring a full-field three-dimensional displacement field and a strain field based on a digital image correlation method guided by a control point and a stereoscopic vision principle; and deformation visualization representation is realized through image splicing and data fusion. According to the invention, non-contact, high-precision and full-field dynamic measurement of the three-dimensional deformation field in the falling and collision process of the whole large aircraft is realized, and technical support is provided for analysis and evaluation of falling adaptability of the aircraft structure and verification of anti-falling and anti-collision design.

The invention provides a side slope deformation video monitoring method and system based on a night vision system, and relates to the technical field of geotechnical engineering safety monitoring. The method comprises the following steps: acquiring all-weather video stream data of a slope area to be monitored through a dual-mode night vision camera device, and preprocessing to obtain a slope deformation image; the slope deformation image is analyzed by adopting a digital image related technology to obtain a slope surface deformation condition, and the slope surface deformation amount is calculated to carry out multi-stage early warning; and inputting the slope surface deformation amount into the trained deformation trend prediction model based on the LSTM, and obtaining the predicted deformation amount for early warning. According to the invention, the bottleneck of night side slope on-line monitoring is broken through, 0.05 mm submillimeter level displacement measurement precision is realized through combination of the visible light-infrared dual-mode camera and the improved video image DIC flow analysis technology, the spatial-temporal feature fusion model is innovatively introduced to improve the early warning accuracy, and a reliable technical means is provided for side slope safety protection in a complex environment.

To provide a system for evaluation that can precisely and easily evaluate the fracture toughness value of a joined body on a joined interface.SOLUTION: The present invention relates to a system for evaluation that comprises: a crack gauge which has its surface coated with a random pattern for a DIC method and is stuck on a joined part for evaluation using a tension testing machine for a joined body; a digital camera which photographs a random pattern; software for analysis which analyses the strain of the joined part; and a computer, wherein the computer can send and receive electric signals between the crack gauge and digital camera, and synchronizes a crack progress length at time X when the joined part cracks that the crack gauge outputs with the strain of the joined part that the digital camera photographs at the time X, and the software for analysis evaluates a progress behavior of the crack at the joined part, and calculates a threshold for determining the progress of the crack based upon the strain at the time X.SELECTED DRAWING: Figure 1

This invention discloses a method and system for real-time stress monitoring during laser additive repair of fatigue long cracks in turbine casings. The method includes: preparing a high-temperature resistant speckle pattern in the pre-treated repair area; simultaneously acquiring a sequence of speckle images and a sequence of temperature field images during the laser repair process; calculating the strain field based on digital image correlation and calculating the real-time stress evolution using thermo-elastic-plastic stress-strain increment theory. The real-time stress value is compared with a dynamic threshold set based on the material's yield strength, and the laser power or scanning speed is controlled based on the feedback of the result to achieve closed-loop control of the repair stress. This invention achieves high-precision real-time online monitoring of stress under extreme repair environments, providing a basis for optimizing and intelligently controlling repair process parameters, effectively suppressing residual stress and the risk of secondary cracks, and significantly improving the repair quality and reliability of turbine casings.