113 results about "Nonlinear deformation" patented technology

The invention relates to the technical field of tunnel engineering, and discloses a tunnel multi-field coupling nonlinear deformation analysis method and system.The method comprises the steps that geological environment information of a tunnel area is collected, a multi-source physical field boundary condition model is built based on collected data, and a heat-seepage-stress-time four-field coupling control model is built based on the collected data; specifying a nonlinear response model for the geological medium to truly reflect the stress-strain behavior of the geotechnical material; solving a coupling equation set, and optimizing the four-field coupling control model; introducing measured data to correct the model; the system comprises a geological data acquisition module, a boundary condition modeling module, a coupling model establishment module, a numerical solution module, a measured data correction module and a visual output and control interface module. According to the method, high-fidelity prediction and evolution analysis of the deformation behavior of the tunnel under the complex geological condition are realized based on comprehensive acquisition of the geological environment, multi-field boundary modeling, control equation construction and numerical calculation.

The invention provides a deformation rate difference-based time sequence InSAR landslide deformation monitoring fusion method, which comprises the following steps of: acquiring and preprocessing a synthetic aperture radar image of a monitoring area to obtain processed SAR image set data, then acquiring a linear deformation rate by using Stacking-InSAR, extracting PS point high-precision deformation speed by using PS-InSAR, and acquiring a nonlinear deformation rate by using SBAS-InSAR; coordinates are generated according to the deformation rate of each technical data point in combination with the orbit and geometric information, and creep, acceleration and temporary sliding deformation areas are divided by using ArcGIS and K-Means clustering; then, SBAS-InSAR processing is carried out on the newly-added image in the regional boundary, and dynamic deformation information is obtained; and finally, carrying out weighted averaging on the deformation rates of the three monitoring technologies. The landslide deformation monitoring precision under complex terrains and environments is effectively improved, errors caused by vector monitoring point density and deformation rate problems in single interference measurement are overcome, and powerful scientific support is provided by accurately monitoring and analyzing landslide evolution, determining the range, predicting the trend and early warning.

The invention relates to the technical field of multi-modal medical image registration optimization methods, in particular to a medical image registration optimization method and system, and the method comprises the following steps: inputting a medical image data set comprising an MRI image data set, a CT image data set and a PET image data set into a trained deformable registration network; obtaining a deformation field by using the deformable registration network; obtaining a final registration result of the two groups of medical image data based on the deformation field, obtaining an optimized final registration result through an iterative optimization algorithm, and obtaining a quality evaluation coefficient at the same time; constructing an optimized objective function by using the quality evaluation coefficient, and realizing the adjustment of the hyper-parameter of the deformable registration network through the back propagation of the optimized objective function; prediction registration is carried out by using the deformable registration network after hyper-parameter adjustment, so that an optimized registration result is obtained, the position and the shape of a convolution kernel are adaptively adjusted based on a feature extraction network of deformable convolution, and nonlinear deformation of a local anatomical structure is better captured.

The invention is suitable for the technical field of earth surface monitoring, and provides an earth surface deformation monitoring method and system based on a time sequence InSAR, and the method comprises the following steps: carrying out the SAR image screening and interferogram generation, and collecting corresponding meteorological data and thermal infrared data; performing space-time adaptive atmospheric phase correction, taking the air pressure vertical gradient and the temperature anomaly as driving factors of atmospheric delay, and separating an atmospheric phase through a space-time weighted model; dynamic deformation modeling is carried out, and deformation is decomposed into linear deformation and nonlinear deformation; the method comprises the following steps: taking a mining area road network as a geometric constraint, unwrapping a coherent region by adopting a minimum cost flow algorithm, converting an unwrapping phase into sight-line-direction deformation, and calculating horizontal and vertical deformation components in combination with InSAR sight-line-direction deformation and a digital elevation model. The method adapts to a complex deformation mechanism of a mining area by capturing linear and nonlinear deformation. Through sight line deformation and DEM geometric projection, vertical and horizontal deformation separation is realized, and the deformation direction is determined.

The invention relates to the technical field of building risk monitoring, in particular to a building safety risk classification method and device and a computer program product. According to the method, based on a permanent scatterer synthetic aperture radar interferometry technology, an SAR image of a monitoring area is calculated to generate InSAR deformation monitoring point cloud data; determining candidate PS points by unifying projection coordinate systems of building vector frame data and InSAR point cloud data and combining a vector frame buffer area and a measuring point height screening method; for the building of which the number of the candidate PS points reaches a preset threshold value, stripping seasonal fluctuation in the deformation data of the building, and extracting a nonlinear deformation trend; based on the nonlinear deformation trend, building a local coordinate system of the building and establishing a differential settlement model, calculating differential settlement indexes of the building in the X and Y directions, and generating a time sequence; by extracting indexes such as the maximum value of the time sequence, the average change rate and the over-limit time proportion, safety risk classification is carried out on the building, and the accuracy of building safety risk classification is improved.

The invention provides a wind power blade aeroelastic coupling modeling method considering a pre-bending shape, which comprises the following steps of: establishing a finite element kinetic equation of a geometric precise beam structure of a pre-bending blade and solving to obtain the section speed of the blade; calculating the inflow velocity according to the section velocity of the blade; calculating a lift coefficient after dynamic stall of the blade; establishing an unsteady aerodynamic load calculation equation according to the inflow velocity and the lift coefficient after dynamic stall of the blade; and constructing a pre-bent blade aeroelastic coupling model according to the unsteady aerodynamic load calculation equation. The method can solve the technical problems that a modeling method in the prior art cannot accurately describe nonlinear deformation of the blade, the continuity of a blade model is poor, the number of calculation units is too large, the calculation efficiency is low, and the modeling method is not suitable for the long flexible blade.

The invention provides a control method and system for improving the blanking precision of an injection mold, and relates to the technical field of injection mold machining. The method comprises the steps that temperature, pressure and displacement multi-source data in the die blanking process are collected in real time; calculating a dynamic deformation compensation coefficient and a blanking stress balance factor based on the data, and respectively representing a material nonlinear deformation trend and a cutting edge stress distribution difference; dynamically adjusting blanking speed, pressure gradient and die temperature field parameters according to calculation results; and through a closed-loop feedback mechanism, a control model is iteratively optimized in combination with a workpiece size error, a die wear compensation step is additionally set, and a stress balance factor is dynamically corrected based on the accumulated blanking times and the cutting edge roughness. The system comprises a multi-source data acquisition module, a dynamic parameter calculation module, a self-adaptive control module and a closed-loop feedback module, and full-process cooperative control is realized. Through multi-physics field data coupling analysis, intelligent parameter optimization and a closed-loop feedback mechanism, the problems of insufficient deformation compensation and out-of-control stress balance in a traditional method are solved.

The invention discloses a radar distributed scatterer interference measurement method and device for a high and steep area. The method comprises the following steps: selecting a main image and a non-main image; calculating differential interference data; screening PS candidate pixels of which the amplitude deviation indexes are smaller than an amplitude deviation threshold value; high-coherence DS candidate pixels are screened out; constructing a distance-constrained Delaunay triangulation network for fusing the PS candidate pixels and the high-coherence DS candidate pixels; resolving a differential residual elevation, a differential deformation rate, a set coherence coefficient of a connected edge and a spatial differential residual phase; calculating residual terrain, linear deformation, deformation rate and residual phase after unwrapping; calculating an atmospheric orbit phase, nonlinear deformation and a noise phase; and obtaining time sequence deformation based on the linear deformation and the nonlinear deformation. According to the method, the number of monitoring points of the orbit descending InSAR deformation monitoring result is large, the coverage range of the monitoring result is widest, and MAE and RMSE are small.

The invention discloses a wind turbine blade semi-coupling aeroelastic modeling method considering nonlinear deformation, and belongs to the technical field of fan simulation calculation. In combination with calculation parameters used by three-party software, establishing a blade structured load model and a blade correction aerodynamic model, calculating an aerodynamic load and a structural load, and superposing: superposing the aerodynamic load, the gravity load and the centrifugal force load of the blade as an external load of a nonlinear structure control equation of the blade, and taking the external load as a calculation parameter; according to the method, the blade nonlinear structure model and the semi-coupling simulation process of the three-party wind turbine simulation software are constructed, and under the same simulation environment and load conditions, the blade nonlinear structure model and the three-party wind turbine simulation software can be subjected to semi-coupling simulation, so that the blade nonlinear structure model and the three-party wind turbine simulation software can be subjected to semi-coupling simulation calculation. The higher-precision non-linear motion response characteristics of the super-long flexible wind turbine blade are calculated, and a good effect can be achieved in the aspects of initial structure design and response evaluation of the large wind turbine blade.

The invention discloses a GNSS (Global Navigation Satellite System) nonlinear deformation correction method based on a full-spectrum three-dimensional thermoelastic model. The GNSS nonlinear deformation correction method comprises the following steps: carrying out discrete Fourier decomposition on a temperature time sequence of each grid point; carrying out space spherical harmonic expansion and coefficient projection on each decomposed frequency; based on a space spherical harmonic expansion and coefficient projection result, considering the periodicity of the temperature, and performing sine / cosine representation of a frequency-by-frequency temperature item; performing spherical harmonic representation and time expansion on the deformed displacement field corresponding to the periodic temperature based on the spatial spherical harmonic expansion and coefficient projection result; solving a deformation equation in spherical coordinates in a Love number form to obtain an expression of a complex Love number; based on the complex spherical harmonic coefficient and the complex Love number of the temperature, full-spectrum synthesis of three-component displacement at the spherical surface is carried out; and performing internal consistency and external dispersion verification based on a full-spectrum synthesis result.

The invention discloses an intelligent detection method and system for a flexible circuit board based on machine vision, and relates to the field of circuit board detection.The method comprises the steps that firstly, through a global coarse registration step, rigid transformation such as translation, rotation and zooming of the whole to-be-detected FPC image is rapidly corrected, and preliminary alignment with a standard template is achieved; then, local fine registration is introduced for nonlinear deformation such as local stretching and wrinkles caused by the characteristics of the FPC material, so that the fine and non-uniform local dislocation is accurately sensed and compensated, and nearly pixel-level accurate matching between the to-be-detected image and the template is realized. On the basis of high-precision alignment, differential attention deficit segmentation is carried out, so that false differences caused by inaccurate deformation registration can be effectively eliminated, real defects can be accurately identified, the false alarm rate is remarkably reduced, and the reliability and practicability of a detection scheme are greatly improved.

The invention relates to the technical field of semiconductors, and discloses a semiconductor defect and yield Map-based automatic calibration method, which comprises the following steps of: acquiring wafer surface data in real time through a multi-modal sensor, analyzing station process parameters, and generating a time-space aligned wafer holographic data set; performing nonlinear deformation compensation based on the wafer holographic data set to generate a dynamic Die grid; utilizing a multi-task deep reinforcement learning model to predict initial Offset parameters of the defect Map and the yield Map; and performing global optimization on the initial Offset parameters through a quantum annealing algorithm, and outputting an optimal Offset. Data are collected through a multi-mode sensor, space-time alignment is carried out through Kalman filtering, a wafer holographic data set of space-time alignment is generated, the data space-time unification is achieved, the wafer state is accurately and completely reflected, and a high-quality data basis is provided for defect analysis and yield evaluation. The problem that data of the multi-modal sensor are inconsistent in time and space and are difficult to effectively fuse is solved.

The invention discloses a rapid deformation reconstruction method for a large-displacement flexible beam structure, and belongs to the field of structural health monitoring. On the basis of a co-rotation coordinate method, the local displacement is obtained after rigid body displacement is removed from the total displacement of the flexible beam structure. Local displacement obtained through a co-rotation coordinate method is substituted into an iFEM formula based on a small deformation hypothesis, and the deformation reconstruction problem under the geometric nonlinear condition is converted into the problem that the mean square error sum of theoretical strain and actually measured strain is minimum by searching an optimal node displacement parameter to achieve square functional optimization. And solving the optimal solution of the functional by adopting an optimization algorithm. In addition, a simplification strategy which ignores a high-order small quantity is adopted, so that the whole nonlinear deformation reconstruction method remarkably improves the calculation efficiency on the premise that the calculation precision is not sacrificed. According to the method, the node displacement parameter enabling the functional to be minimum can be rapidly solved, and rapid and high-precision deformation reconstruction of the large-displacement flexible beam structure is achieved.

The invention relates to the technical field of intelligent printing quality detection, in particular to an intelligent printing quality detection method based on image recognition. The system comprises an image preprocessing module, a physical model construction module, a deformation iterative calculation module, an energy decoupling analysis module and a closed-loop feedback control module. The method comprises the steps of generating a feature point matrix and a to-be-detected feature field by acquiring standard and real-time image data; the core of the method is to construct a virtual tensor spring network model, map image differences into an external acting force field, and solve deformation potential energy distribution by using finite element iteration; a Laplace operator is adopted to execute energy decoupling, low-frequency isotropic stress and high-frequency topological potential energy singular points are separated, and a residual thermodynamic diagram is generated according to the singular points to position defects and adjust transmission tension; according to the method, the transformation from pure image comparison to physical potential energy evolution is realized, the mutual exclusion limitation of deformation tolerance and detection sensitivity is broken through, and the nonlinear deformation interference in the high-speed transmission of the flexible material can be effectively filtered.

The invention discloses an enhanced Swinin-Unet liver tumor segmentation method fusing blood vessel guidance and adaptive deformation attention. Through combination of elastic B-spline registration and affine transformation, nonlinear deformation is compensated, a multi-modal image space alignment error is reduced, and tumor boundary blur and feature dislocation are reduced. Topological features are extracted in combination with a blood vessel reconstruction module, and model attention is effectively guided. The encoder adopts a convolution pool and a deformable attention SADR down-sampling, and a lightweight deformable attention module is integrated through jump connection, so that effective multi-scale feature fusion and space alignment are realized, and the model perceptibility is enhanced. The graph theory model is embedded into liver lobe partition and blood vessel curvature constraint, and it is ensured that the segmentation result is strictly matched with blood vessel blood supply topology. In order to solve the class imbalance problem, an FA loss function is provided and combined with a structure correction algorithm (SGDR), so that incomplete segmentation and false positive artifacts are effectively reduced. Experimental verification on a LiTS data set shows that the method is superior to an existing method in liver and tumor segmentation, and Dice coefficients reach 93.38% and 91.39% respectively.

The invention provides a nonlinear finite element discrimination method for a critical stable section of an underground cavern, and the method comprises the steps: determining a rock mass strain softening parameter according to a rock mass mechanical test in actual engineering; performing secondary development on a rock mass constitutive model based on the rock mass strain softening parameters; based on the rock mass constitutive model after secondary development, a nonlinear finite element initial model for solving the critical stable section of the underground cavern is constructed; the nonlinear finite element model is solved, and the overall tangent rigidity of the model in the calculation time step is obtained; based on the overall tangent stiffness, calculating to obtain a minimum characteristic value of an overall tangent stiffness matrix; and based on the minimum characteristic value, distinguishing the critical stable section of the underground cavern. The method directly and quantitatively reflects the essential characteristics of rigidity loss and bearing capacity reduction of the whole cavern structure system after a complex nonlinear deformation path including strain softening is considered, so that the critical instability moment and the potential instability section are accurately captured.

The invention relates to an image registration method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a first image and a second image obtained through image collection of a target physiological region, the first image data being a three-dimensional image, and the second image being a two-dimensional image; and determining a deformation field describing a mapping relation between the first image and the second image, and performing nonlinear deformation on the first image according to the deformation field to obtain a deformed image. And projecting the deformed image to obtain a two-dimensional third image capable of measuring a registration effect with the second image. According to the embodiment of the invention, through the architecture for image deformation and projection and image registration based on the deep learning automatic learning deformation field, the elastic registration between the images can be simply, quickly and accurately realized. Meanwhile, the image registration mode is realized by depending on a software algorithm without depending on the improvement of a hardware structure, so that the cost is low.

The invention discloses a landslide deformation prediction method and system combining multi-source data and residual optimization, and belongs to the technical field of landslide deformation monitoring. According to the method, multi-scale spatial-temporal characteristics are extracted through a CvT model to realize preliminary prediction, an xLSTM model with GNSS as external guidance is innovatively introduced to carry out dynamic time sequence modeling and compensation on prediction residual errors, and finally a high-precision displacement prediction value is output through residual error optimization. According to the method, dynamic deep fusion and closed-loop correction of InSAR large-range monitoring and GNSS high-precision data under a deep learning framework are realized, and the key technical bottlenecks of system error accumulation, insufficient multi-source data collaboration and limited nonlinear deformation modeling precision in the existing method are effectively solved; the accuracy, the stability and the physical credibility of landslide prediction are remarkably improved, and the method has outstanding technical advancement and practical value.

The invention relates to the technical field of image processing, in particular to a positioning method for lamination of multi-layer flexible materials based on machine vision, which comprises the following steps: acquiring images of a first flexible material to be laminated and a second flexible material serving as a reference; contour geometry and surface texture features are extracted in parallel for the image, and a first feature map and a second feature map with the features as nodes and the spatial topological relation and gradient mutual information as weighted edges are constructed; calculating an initial nonlinear deformation field of the first flexible material; utilizing the initial nonlinear deformation field guide graph matching algorithm to obtain rough matching feature point pairs; and further solving to obtain a final non-rigid transformation model, and generating positioning parameters including non-uniform scaling and local distortion to guide fitting operation. According to the invention, the quality and efficiency of the flexible material laminating process can be improved.

The invention relates to the technical field of machine vision and optical measurement mechanics, and discloses a deformation identification and measurement method based on machine vision and deep learning, and the method comprises the following steps: S1, system calibration and base library construction; s2, offline training of the hybrid model; s3, real-time decoupling and coefficient regression are carried out; and S4, final assembly and physical quantity calculation of the deformation field. According to the method, a deformation field is decoupled into a global nonlinear deformation field () and a residual deformation field () through S3, and the global nonlinear deformation field () and the residual deformation field () are superposed. The physical significance and the stability of a deformation main body are ensured by utilizing the physical deformation base library constructed in S1 and model reconstruction; meanwhile, a luminosity residual image () generated in the S3 is used for driving module reconstruction, local high-frequency disturbance which is not covered by a physical model is accurately compensated, a high-dimensional deformation field is decoupled into low-dimensional global physical prior regression and residual correction, and efficient real-time measurement is achieved; meanwhile, numerical difference is replaced by analytic derivation, so that the signal-to-noise ratio and the measurement precision of the strain field are remarkably improved.

The invention discloses an image correction, recognition and information retrieval method and a related device, a single-page document area is detected from a target document image, a single-page document image containing the single-page document area is obtained, interference of attached pages or other page contents in the target document image is avoided, and the image correction effect is improved. According to the method, the physical deformation correction model is configured, the mapping information used for describing the mapping relation between the pixel points in the single-page document image and the pixel points in the corrected flat image can be output on the basis of the input single-page document image, and the physical deformation correction model is more good at processing complex nonlinear deformation, so that the image quality is improved. According to the method and the device, various physical deformation (wrinkles, bumps and the like) can be identified, and the prior knowledge of the document content can be implicitly learned to assist correction, so that the correction effect on the document image with the physical deformation is improved. And the effect of subsequent image recognition related tasks can be improved.

The invention discloses a ground-air-pipe multi-dimensional coupling PCCP pipeline health monitoring system and method, and belongs to the technical field of underground pipeline safety monitoring, and the system comprises an InSAR air monitoring unit, an artificial corner reflector array and a distributed optical fiber sensing unit. The PCCP pipeline is monitored from the air through the InSAR technology, and ground surface settlement rate abrupt change points and non-linear deformation areas are extracted through InSAR time sequence analysis; an adjustable artificial corner reflector is arranged along a vertical projection area of the pipeline, so that the phase incoherence problem of the InSAR technology in pipeline monitoring is improved, and the InSAR phase stability is enhanced; distributed optical fibers are pre-buried in the PCCP manufacturing stage and used for collecting pipe body strain data in real time, an abnormal space correlation map is constructed in combination with InSAR time sequence analysis data, and the hidden damage position and probability of an underground pipeline are deduced and inversely deduced through Bayesian causality. Omni-directional and multi-dimensional health monitoring from the ground and the air to the pipeline is achieved, the monitoring precision and reliability are effectively improved, and a powerful guarantee is provided for safe operation of the PCCP.

The invention relates to the technical field of underground engineering, and discloses a construction safety assessment method, system, equipment and medium for a shield tunnel, and the method comprises the steps: quantifying a construction load and a foundation coefficient in a current construction step, inputting the quantified construction load and foundation coefficient into a nonlinear mechanical solving framework composed of a longitudinal multi-ring model and a single-ring variable model, and carrying out the processing. The longitudinal deformation quantity of each beam unit is obtained, when the longitudinal deformation quantity does not meet the preset requirement, the quantification process of the longitudinal deformation quantity is repeatedly executed until the preset requirement is met, and the bending and shearing modes of each beam unit are determined according to the single ring deformation model so as to evaluate the safety state of the current construction step; the current construction step is updated to iteratively execute the evaluation process of the safety state in the updated current construction step until all construction steps are completed, and a safety evaluation result of the shield tunnel under the action of the construction load is obtained; and the nonlinear deformation response in the longitudinal direction of the shield tunnel is accurately solved, and comprehensive and accurate safety evaluation of the shield tunnel is realized.

This invention proposes a cross-coordinate system road network data fusion method based on hierarchical matching and non-rigid registration, belonging to the field of road network technology, and solves the problems of computational complexity and poor versatility of existing methods. The method includes: acquiring and preprocessing benchmark and target road network data; estimating global transformation relationships by calibrating feature points, and initially aligning the benchmark road network to the target coordinate system to obtain a global region; constructing a fixed image of the target road network and a moving image of the benchmark road network within the global region; using algorithms such as B-spline free deformation that can model local nonlinear deformations to perform non-rigid registration on the fixed and moving images, optimizing the cost function to obtain pixel-level deformation fields; geometrically correcting the benchmark road network based on the deformation field, transferring the target road network attribute information, and summarizing and outputting a fused dataset. This method improves local matching accuracy and versatility through a hierarchical strategy and pixel-level registration, overcoming the influence of differences in road segmentation.

The invention discloses a mechanical driving system and method for facial expressions, and belongs to the technical field of bionic robots. The system comprises a stress response unit, a mechanical chaos engine and an expression execution mechanism. The stress response unit adopts a design structure that an arc-shaped elastic sheet is in bridge connection with an elliptical ring, converts external mechanical force into nonlinear deformation and realizes automatic resetting; the mechanical chaos engine takes mechanical tolerance as an internal random source, realizes multi-physics field coupling and chaos amplification through a three-stage driving structure, and drives an expression execution mechanism composed of a gradient hardness material, an asymmetric groove array and an intercommunication ring. According to the method, by sensing external force input, a chaos engine is excited to generate unpredictable, natural and rich facial random expressions. Controllable expression of emotional tendency is achieved through a pure mechanical structure, and static and dynamic expressions reflecting the emotional change process can be output. The system is simple and compact in structure, the method randomness is reliable, and the method is suitable for the fields of robots, intelligent toys, emotion counseling, man-machine interaction and the like.

The application discloses a structure nonlinear deformation reconstruction method and system based on isogeometric and reduced basis, and the method comprises the following steps: measuring initial strain data of a ship plate structure surface, constructing a plurality of four-node inverse shell elements of the ship plate based on the initial strain data; assembling the plurality of four-node inverse shell elements to obtain a whole stiffness matrix; reconstructing the whole stiffness matrix based on the measured strain data of the ship plate to obtain a linear reconstruction result of the ship plate; correcting the linear reconstruction result based on the reduced basis, and fusing the correction increment to the linear reconstruction result for nonlinear iteration to complete nonlinear deformation reconstruction. On the basis of the principle of isogeometric analysis, the application combines the inverse finite element method to establish a four-node inverse shell element, realizes high-precision ship structure displacement reconstruction through a small number of strain measuring points, and helps designers to intuitively understand and deeply understand the mechanical properties of the structure and to monitor the safety of the structure in real time.

A method for calculating the in-plane nonlinear deformation of an arch structure with axial defects in a Cartesian coordinate system is presented. This method is based on two states of the arch structure's curve element in the Cartesian coordinate system: an ideal axis and an actual axial defect. It derives the changes in the arc length and curvature of the curve element before and after deformation, obtaining expressions for the nonlinear compressive and bending strains in the in-plane of the arch structure with axial defects in the Cartesian coordinate system. The method also derives the nonlinear equilibrium differential equations in the in-plane of the arch structure with axial defects in the Cartesian coordinate system, obtaining solutions that satisfy the mechanical and geometric boundaries of the arch structure with axial defects. Finally, the method derives the nonlinear equilibrium governing equations in the in-plane of the arch structure with axial defects, ultimately obtaining the solution to the nonlinear mechanical problem in the in-plane of the arch structure with axial defects in the Cartesian coordinate system. This method can obtain the essence of the nonlinear mechanical problem of the arch structure with axial defects in the Cartesian coordinate system, filling the gap in the nonlinear strain-displacement expression for the in-plane of the arch structure with axial defects in the Cartesian coordinate system.

The object of the present invention, which relates to a method for printing a substrate by means of inkjet printing, is to enable accurate printing of a bonding point matrix with less complexity than an ideal orthogonal bonding point matrix by shifting, rotating or deforming it, in particular by nonlinear deformation. This object is achieved in that the bonding areas of a bonding area line are determined relative to the nozzle lines by selecting a lateral resolution that is sufficiently large so that the minimum distance between nozzle lines is smaller than the minimum distance between bonding area rows, and by varying (deforming) the distances between adjacent bonding area rows between the various bonding area lines specified by the substrate, and thus only the print head nozzles having nozzle lines intersecting the bonding areas are actuated according to the nozzle actuation scheme and the corresponding bonding area type.

The invention discloses a small-scale deformation InSAR time sequence inversion method and system based on multiple stable points, and the method comprises the following steps: S1, carrying out the small baseline interference processing of multi-temporal synthetic aperture radar data, and screening high-coherence pixel points, S2, recognizing a stable point candidate set with dense spatial distribution; s3, constructing an initial atmospheric delay phase model covering a full interferogram range; s4, obtaining an interferometric phase after atmospheric correction; and S5, inverting the deformation rate and the deformation time sequence parameters of the InSAR again. According to the method, dense stable points are screened based on a deformation rate threshold value, and a space atmosphere model is constructed, so that the problem that atmosphere delay and nonlinear deformation are difficult to separate in InSAR time sequence analysis is effectively solved, and high-signal-to-noise-ratio and high-precision time sequence monitoring of small-scale weak deformation of the earth surface is realized.

This invention discloses an adaptive adjustment device and method for tool holes in a high-precision circuit board alignment system. The device includes an upper camera group, a lower camera group, and multiple PIN adjustment units. The upper camera group acquires images of a target on film, while the lower camera group acquires images of the tool holes on the circuit board. The theoretical coordinates of the current part number are loaded, and the dual cameras are simultaneously triggered to acquire images and calculate the actual offset vector of each tool hole. When the offset exceeds a preset threshold, the theoretical position of the tool hole is used as the control point. A nonlinear deformation field is reconstructed using the radial basis function of a thin-plate spline, and the displacement compensation amount of each PIN adjustment unit is calculated based on the deformation field, driving each PIN unit to move to the target position. The flexible conical PIN head is coated with a PEEK coating and, in conjunction with a force sensor, achieves adaptive force-controlled insertion, automatically correcting the center offset. This method can accurately compensate for the nonlinear deformation and temperature drift of the circuit board, reduce tool hole wear, and improve changeover efficiency and alignment accuracy.