21 results about "Defect reconstruction" patented technology

The invention discloses an industrial detection metal part internal tiny defect quality evaluation method, and relates to the technical field of metal part quality detection, and the method comprises the steps: employing a Peephole-LSTM model to carry out the dynamic weight distribution of the credibility coefficient of multi-modal data, carrying out the fusion, generating a defect feature pattern of a metal part, and carrying out the calculation of the defect feature pattern of the metal part; carrying out local CT scanning based on the defect feature map of the metal part to obtain metal part defect reconstruction data, calculating the equivalent diameter, the maximum sectional area and the volume of the metal part defect based on the metal part defect reconstruction data, obtaining defect quantization parameters, and calculating the defect quality score of the metal part according to the defect quantization parameters. And dividing quality grade intervals for comparison based on the defect quality score of the metal part, and obtaining a quality evaluation result of the metal part. According to the metal part quality evaluation method, the safety and reliability of the high-precision advanced equipment metal part in actual service are effectively guaranteed.

The invention provides an additive repair blade high-cycle fatigue limit prediction method based on random defect probability distribution, and relates to the field of aero-engine fan and compressor blade maintenance, and the method comprises the steps: obtaining the defect distribution of a real blade; establishing a prediction model based on a critical distance theory; according to the prediction model, critical distances of the multiple real blades are determined, and a first critical distance is generated; performing defect reconstruction based on the defect distribution of the real blade to generate a virtual blade; obtaining the first high-cycle fatigue strength of the virtual blade according to the defect distribution of the virtual blade, the first critical distance and the prediction model; respectively determining a plurality of defect parameters and a Pearson coefficient of the first high-cycle fatigue strength, and screening a first parameter significantly related to the first high-cycle fatigue strength; constructing a fatigue strength evaluation model; and inputting the first parameter into the trained fatigue strength evaluation model, and outputting the predicted high-cycle fatigue strength. According to the scheme, the high-cycle fatigue limit of the blade can be quickly predicted, and the prediction accuracy is improved.

The invention discloses a multi-data fusion boiler pipeline outer wall defect detection method and system, and belongs to the technical field of boiler pipeline defect detection.The method comprises the steps that three types of original data of the outer wall of a boiler pipeline are obtained; if the data are point cloud data, converting the data into a depth map; performing feature extraction on the three types of original data through three independent encoders of a multi-branch feature extraction layer, and performing channel standardization and scale alignment operation through a standardization layer after extraction to obtain corresponding visible light features, infrared features and depth features; adaptive fusion is carried out through a cross-modal attention mechanism of a cross-modal feature fusion layer, and fusion features are obtained; performing feature processing through the multi-scale residual fusion layer, and outputting a defect region mask; and performing three-dimensional defect reconstruction based on the depth map and the defect area mask to obtain a detection result of the boiler pipeline outer wall defect. According to the invention, high-precision and high-robustness defect detection under complex working conditions can be realized.

The invention relates to the technical field of data processing, in particular to a 3D printing material defect detection method and system based on multi-sensor fusion. The method comprises the steps of capturing thermal radiation flux and a pose change track, extracting thermodynamic divergence and a transient motion vector, constructing a spatial delay compensation coefficient by combining a heat exchange dissipation coefficient, generating a priori estimation set by a feedforward correction state prediction matrix, constructing a divergence suppression factor according to a transient temperature change rate, and multiplying the divergence suppression factor into a covariance prediction link. Filtering to generate a posterior estimation set, extracting a reflectivity optical gradient for cross-domain verification, mapping an optical reference and calculating a residual matrix, superposing a high-frequency residual to the posterior estimation set, generating a defect reconstruction set, and analyzing the set to output defect space coordinates and morphology distortion information. According to the invention, the printing material defect detection precision is obviously improved.

The application discloses a kind of based on CT scanning image's additive repair blade fatigue failure analysis method.Combining the way of CT technology and optical microscope is used to carry out defect test analysis and crack imaging to additive repair titanium alloy blade, establish the correlation law between the defect characteristics of titanium alloy blade additive repair area and fatigue performance.First, utilize high-resolution CT technology to carry out nondestructive testing to blade, carry out global defect reconstruction to the leading edge of additive repair titanium alloy blade, obtain the distribution characteristics of defect parameters by statistical analysis;Analysis of defect-related fatigue source and crack propagation behavior, combined with defect-dependent additive repair blade high-cycle fatigue life (limit) model, establish a kind of fatigue failure analysis method based on CT scanning image.Through the method, key defects can be accurately identified and its influence on blade service life is predicted, so as to provide scientific basis and theoretical guidance for repair and reuse of aero-engine blade.

The invention discloses an iliac defect reconstruction device and a preparation method thereof, the iliac defect reconstruction device comprises an implant, the implant comprises a biological implant, the shape of the biological implant is matched with the shape of a bone defect part; the memory metal bracket is embedded in the biological implant; the memory metal stent is formed by mutually connecting a plurality of tubular structures; wherein the memory metal stent can be molded into a first form at a first temperature, and is embedded and mounted in the biological implant in the first form; the memory metal stent deforms into a second form at a second temperature so as to generate stress stimulation on the biological implant; the first temperature is lower than the second temperature; and an embedding groove matched with the first form is formed in the biological implant. The ilium defect reconstruction device provided by the invention has multiple functions of personally adapting to a bone defect part, stimulating new bone growth and mechanically stabilizing.

The application discloses a kind of based on computer vision fan blade defect detection method and system.In the computer image vision detection of fan blade, due to the shooting angle of camera and fan blade itself is the solid structure with curvature, will cause the image of fan blade shooting to produce distortion, to affect the precision of defect identification.Therefore, the application corrects the shooting image of fan blade according to the curvature of fan blade by adopting Mosaic data enhancement technology, to improve the analysis precision of subsequent blade defect.In addition, the application also improves the detection efficiency of blade visual image by introducing attention module CBAM;By improving the three-dimensional reconstruction method of defect, the three-dimensional defect reconstruction precision of fan blade is further improved;By subsequent introduction of laser detection equipment and ultrasonic detection equipment, the accuracy of blade defect detection is further improved by using fusion judgment method.

The invention belongs to the technical field of defect detection, and particularly relates to a defect reconstruction method applied to phased array ultrasonic detection of a spinning shell. Aiming at the problems of difficulty in feature extraction and multi-direction detection and reconstruction of spinning textures in phased array ultrasonic detection of spinning shell defects, noise interference caused by the spinning textures is effectively inhibited by adopting a multi-channel blind separation processing method provided by the invention, and the feature echo extraction effect is improved; and in combination with data in four directions, a position reconstruction algorithm based on a geometrical relationship is established, and reconstruction of a workpiece structure and defects is realized.

The invention discloses a plastic production quality defect detection method based on image detection, and relates to the technical field of image detection, and the method comprises the following steps: executing refractive index estimation and light path inversion calculation on light offset characteristics, and generating a light path correction image; performing illumination normalization, local contrast enhancement and texture gradient extraction on the light path correction image to form a candidate area image containing a defect candidate area; and inputting the candidate region image into a self-supervised reversible reconstruction network for secondary reconstruction to generate a corresponding candidate region reconstruction image, and calculating a defect reconstruction difficulty score based on a pixel residual between the candidate region image and the candidate region reconstruction image. According to the method, the candidate region image is input into the self-supervised reversible reconstruction network, and the defect reconstruction difficulty score is constructed based on the reconstruction error, so that the refined quantitative expression of the authenticity performance of the candidate region in the image detection process is realized.

The invention relates to the technical field of nondestructive testing and intelligent signal processing, in particular to a reinforcing steel bar signal suppression and reinforced concrete structure defect reconstruction method and system. Feature modeling is carried out through a Transform architecture, a dynamic attention mask mechanism is introduced, explicit modeling and suppression are carried out on steel bar echoes, meanwhile, defect related features are enhanced, and the problem that defect information is prone to being lost due to the fact that a traditional method depends on artificial experience parameters or simple filtering is solved. Meanwhile, weak reflection defect signals such as cracks and cavities in the concrete are enhanced and spatially reconstructed on the basis of inhibiting the interference of the reinforcing steel bars, so that a reconstruction result has higher definition and interpretability, and the imaging quality and defect identification reliability of the ground penetrating radar in a complex reinforcing steel bar environment are improved. Besides, an end-to-end trainable network structure is adopted, so that the method has good generalization ability and anti-noise performance, can adapt to detection scenes in different structural forms and different construction environments, and has high engineering application value.

The invention discloses a 3D printing Ti metal bone trabecular acetabulum reconstruction pile and an operation method thereof, the 3D printing Ti metal bone trabecular acetabulum reconstruction pile comprises a plurality of reconstruction piles corresponding to the ilium, the pubis and the ischium, and adaptive acetabular cup prostheses are arranged between the reconstruction piles; the reconstruction pile comprises a pile body, one end of the pile body is a conical head end, the other end of the pile body is a tail end, a hollow hole channel allowing a guide pin to penetrate through is formed in the pile body in the axial direction, holes are distributed in the side wall of the pile body, and the stable foundation of the acetabulum is expanded to normal sclerotin of the ilium, the ischium and the pubis. The reconstruction pile is arranged in the medullary cavity of the part to form stable support, the bone cement is connected with the acetabular cup prosthesis, the shape and degree of acetabular bone defects do not need to be considered, the method is suitable for reconstruction of all types of acetabular bone defects, and the problem that a traditional method is limited in adaptation range is solved.

The present application relates to the technical field of image data processing and three-dimensional image reconstruction, and discloses a complex curved surface pipe defect reconstruction method, system and medium, comprising: collecting annular multi-view projection fringe images of a complex curved surface pipe, generating fringe images and initial three-dimensional point clouds, and converting the point clouds to a unified three-dimensional coordinate system under a clamp reference; extracting fringe centers, recording fringe image quality data and collecting optical path data; reconstructing a defect-free reference pipe curved surface based on a point cloud with measurement data and determining reference curved surface data; calculating point cloud measurement reliability and pipe curved surface defect residual determination values according to fringe image quality data, collecting optical path data, reference curved surface data and signed normal residual, generating a defect starting point set, a defect connected region and a defect boundary; performing secondary curved surface reconstruction in the defect connected region to obtain defect area reconstruction point clouds, and generating a complex curved surface pipe defect three-dimensional model and a single-channel defect depth map.

The present application relates to a kind of bridge underwater pile pier structure defect reconstruction methods based on laser scanning device, including laser scanner and with laser scanner connection and drive its with annular first guide rail sliding drive unit, first guide rail vertical sliding connection in a detection frame, second guide rail is fixed on the inner wall of detection frame and is extended vertically to be used for the sliding of first guide rail, the second guide rail is vertically provided with screw rod and first guide rail is driven to slide by it, the depth data of pile pier apparent defect site is obtained by the above device, data is processed in combination with coordinate conversion, reconstructs the damage location, shape and depth of pile pier, reconstructs the apparent defect of bridge underwater pile pier structure, and then can establish numerical model to calculate and analyze.It is compared with prior art reconstruction method, the numerical model corresponding to the pile pier structure with defect can be established by the present application, to provide reliable technical support for the safety evaluation and maintenance of bridge structure.

The invention discloses an ultrasonic three-dimensional nondestructive testing method based on multi-probe echo data joint calibration, and relates to the technical field of material detection, and the ultrasonic three-dimensional nondestructive testing method comprises the following steps: S1, multi-source data space collaborative calibration; s2, echo signal feature extraction and joint optimization; s3, performing multi-view synthetic aperture three-dimensional imaging; and S4, three-dimensional defect automatic identification and quantification. According to the ultrasonic three-dimensional nondestructive testing method based on multi-probe echo data joint calibration, probe poses and acoustic axis errors are corrected by introducing a reference reflection module, and signal consistency is improved by combining empirical mode decomposition, depth gain compensation and cross-correlation phase alignment; and high-precision defect reconstruction and quantification are realized by adopting angle weighted full-focus imaging and three-dimensional watershed segmentation, so that the problem of insufficient three-dimensional imaging precision caused by space reference deficiency, echo inconsistency and unreasonable fusion weight of a multi-probe system can be effectively solved.

The present application belongs to the technical field of optical surface defect detection, and particularly relates to a surface micro-defect reconstruction method based on scattered light flight time difference. The present application is directed to the problems that the current dark field scattering defect detection system has low utilization rate of multi-dimensional information of light field, cannot directly measure the defect size, classify the defects, and avoid the crosstalk caused by the secondary or multiple reflections of incident light on the surface, and proposes a calculation method for reconstructing the geometric characteristics of surface micro-defects based on scattered light flight time and a corresponding three-dimensional reconstruction model. According to the relative spatial pose relationship of the light source-defect-detection point, the present application focuses the source of calculation data on the process that the light beam is first contacted with the object surface from the light source, and skillfully uses the scattered light flight time difference to avoid the discussion of multiple interactions such as multiple scattering of the light beam and the object surface, thereby improving the detection capability of the dark field scattering detection system for the geometric characteristics of surface defects from the principle level.

The invention discloses a volume calculation and geometric reconstruction method, device, equipment and medium for a road internal disease, and the method comprises the steps: carrying out the standardization processing of three-dimensional simulation point cloud data of the road internal disease, and obtaining the standardized simulation point cloud data; the method comprises the following steps: preprocessing data, identifying disease connected sub-regions, determining an internal starting point to construct a starting point set, constructing a space stepping direction based on the starting point set, performing stepping search to judge boundary points, generating a boundary point set, fusing the boundary point set to obtain a disease space contour, and completing disease volume calculation and three-dimensional geometrical shape reconstruction based on the disease space contour. According to the method, the internal starting point constraint is combined with the multi-direction stepping search to accurately position the disease boundary, the boundary points are fused to recover the complete disease geometry, the topology reconstruction and volume calculation of the complex disease network are accurately realized, the problems of incomplete boundary of the disease point cloud and complex topology of the complex disease in the road are effectively solved, and the method is suitable for large-scale popularization and application. And the disease reconstruction integrity and the volume calculation precision are improved.

The invention discloses a method, device and equipment for reconstructing internal defects of a multi-layer non-magnetic metal structure, and the method comprises the steps: heating the multi-layer non-magnetic metal structure through a coil, and obtaining a thermal image sequence; determining a surface plate temperature distribution matrix based on the thermal image sequence; reconstructing the initial conductivity distribution matrix of the inner-layer plate based on the temperature distribution matrix of the surface-layer plate to obtain a conductivity distribution matrix of the inner-layer plate; and taking the conductivity distribution matrix of the inner layer plate as a reconstructed image, and determining a defect area based on the reconstructed image. The invention aims to solve the problem that an existing eddy current thermal imaging method cannot realize inner layer defect reconstruction of a multi-layer structure.

The invention belongs to the technical field of composite material manufacturing, relates to a method and a device for inhibiting internal defects in curing forming of a carbon fiber composite material vacuum bag, and aims to solve the problem of energy intervention blindness caused by lack of real-time sensing and response capability for defect generation dynamics in the prior art. According to the method, on the basis of the synergistic effect of terahertz in-situ imaging and ultrasonic targeted intervention, through four-stage closed-loop control of real-time monitoring, defect reconstruction, decision positioning and in-situ repair, space-accurate and parameter-adaptive repair is carried out on submillimeter pores, cracks or layering defects before resin gelation; the matching device integrates a terahertz detection module, an ultrasonic vibration module and a five-axis linkage positioning mechanism, and adopts mutual exclusion time sequence control to avoid multi-physics field interference. Through the scheme, the consistency of the internal quality of the composite material and the qualified rate of finished products can be remarkably improved on the premise of not disturbing fiber orientation.

This invention discloses a quantitative non-destructive testing method for defects in plate structures. The method includes: performing ultrasonic testing on the metal plate to be tested to acquire the measured signal; inputting the initial velocity model of the metal plate to be tested and the measured signal into a full waveform inversion algorithm for one iteration update to obtain the updated velocity model of the metal plate to be tested; converting the updated velocity model into a thickness model and inputting the thickness model into a trained defect reconstruction model to obtain the defect reconstruction result of the metal plate to be tested; the defect reconstruction result includes the location, size, and shape information of the defect; this invention utilizes a trained defect reconstruction model based on a full waveform inversion to accurately detect defects, thereby improving the defect detection capability in plate structures.

Compositions and methods are provided for lamellar and defect reconstruction of corneal stromal tissue using biomaterials that form a defined hydrogel structure in situ, including interpenetrating (IPN) and semi-IPN hydrogels.

The invention discloses a SiCp / Al composite material complex part lightweight additive manufacturing method based on a defect reconstruction and topological optimization algorithm. A gyandroid filling lattice structure is used for replacing a local defect area, and light weight of parts is achieved. The method comprises the following steps: firstly, printing a batch of samples, performing in-situ monitoring, calculating size proportions and volume fractions of defects in different directions by applying a three-dimensional defect reconstruction algorithm, and determining optimal process parameters; secondly, the optimal parameters are used for preliminarily printing the complex part, internal defect distribution of the complex part is obtained, defect reconstruction data is coupled with a topological optimization algorithm, and a gyandroid filling lattice structure is used for replacing a local defect area to achieve lightweight design; and finally, printing a final part by using the optimized parameters and structure. According to the method, the optimal process parameters can be rapidly determined, the structure is dynamically adjusted through defect reconstruction and topological optimization coupling, and efficient light-weight manufacturing of the SiCp / Al composite material complex part is achieved on the premise that functionality and reliability are guaranteed.