38results about How to "Improve numerical stability" patented technology

The invention discloses an industrial robot motion pose error calibration method based on constraint solution. The industrial robot motion pose error calibration method comprises the steps that S1, joint angles, tail end coordinates and temperature data of multiple measurement points are collected; s2, correcting the kinematic model by using the thermal elongation and constructing a parameter identification model; s3, constructing a mixed integer nonlinear constraint pool according to mechanical limitation; s4, introducing a semi-definite programming slack variable to convert the non-convex constraint into a linear matrix inequality; s5, combining a primal-dual interior point method and an alternating direction multiplier method to iteratively solve the optimal kinematics parameter correction; s6, introducing a square root information filtering improvement mechanism to correct a state vector square root factor, and calculating an updated nominal kinematics parameter; and S7, based on the condition number of the error Jacobian matrix, judging observability and repeatedly calibrating. According to the method, the problem of precision reduction caused by thermal errors is solved, and the identification precision, the numerical stability and the self-adaptive calibration capability of the kinematics parameters of the robot are improved.

This invention relates to a method and system for gyroscope attitude estimation and error compensation based on SO(3) complementary filtering. The method includes: establishing an attitude estimation model on the SO(3) group, representing the carrier attitude as an estimated rotation matrix satisfying orthogonal constraints, and designing a cost function that includes accelerometer and magnetometer information; collecting sensor data from the inertial measurement unit; calculating the corrected angular velocity based on the cost function and the current sensor measurement values, and converting the sensor measurement deviation into a correction amount on the SO(3) group using vector cross product operation; using the corrected angular velocity to estimate and update the gyroscope zero bias online, and performing real-time tracking and compensation for gyroscope drift; performing matrix exponential mapping operation on the compensated angular velocity using the Rodrigues formula to achieve incremental updates of the rotation matrix while maintaining SO(3) manifold constraints; and outputting the estimated attitude information and gyroscope zero bias. This invention improves numerical stability and computational accuracy.

This invention discloses a hybrid inverse kinematics method for rotating biprisms that deeply integrates deterministic physics prior models with reinforcement learning. It solves the long-standing problem of balancing computational efficiency and pointing accuracy in existing rotating biprism beam pointing inverse kinematics techniques. This invention employs a reinforcement learning compensation method based on the paraxial approximation method, preserving its computational efficiency. The paraxial approximation method solves the problem through basic arithmetic operations, a single inverse trigonometric function, and simple conditional judgments; the number of operations remains constant regardless of the input parameters, resulting in a time complexity of O(n log n). Spatially, the paraxial approximation method requires only a small number of scalar variables, resulting in a space complexity of O(n log n), lower memory usage, and better numerical stability.

The invention discloses a three-dimensional FDTD metal conformal stabilization simulation method. The method comprises the steps of grid construction and boundary identification, effective electromagnetic parameter calculation, stability condition pre-verification, field quantity iteration updating and boundary condition convergence judgment. According to the method, high-precision and high-stability electromagnetic simulation of a complex medium boundary and a metal boundary is realized by combining an integral form of the effective dielectric constant and the magnetic conductivity, a posterior weighted stabilization strategy and a strict integral updating rule of the metal boundary, meanwhile, the robustness of an algorithm to a time step length is improved, and the practical application scene of the method is expanded.

This invention discloses a method and system for calculating the etching factor and copper layer thickness based on point cloud data. For the input point cloud data, median filtering is used to remove local outliers, followed by uniform filtering to smooth the overall trend. The rising or falling trend of the Z value is detected by calculating local gradients, and layer switching points are identified by detecting the difference between adjacent gradients. Based on these layer switching points, the point cloud data is physically classified into copper layers and PI layers. The spatial coordinates of each layer are extracted for subsequent benchmark fitting. A copper layer benchmark curve is established using Chebyshev polynomial fitting. The offset between the actual measurement point and the benchmark curve is calculated, separating the systematic deviations of the copper and PI layers. Finally, the true thickness is obtained through benchmark alignment. This method can approximate the layer curvature with minimum and maximum errors within a given interval, making it particularly suitable for the nonlinear characteristics of curved circuit board surfaces. Furthermore, its numerical stability is superior to standard polynomials, avoiding the Runge phenomenon.

This invention discloses a method for temperature control of a rotary lime kiln based on neural network prediction, belonging to the field of industrial process control technology. The method acquires historical process parameter data during the operation of the rotary lime kiln and preprocesses the data; constructs and trains a dual-path neural network prediction model, learning the temporal evolution of the system state and the influence of control quantities on the state through independent paths, and explicitly superimposing the two to predict the operating state parameters of the rotary lime kiln in future control cycles; constructs a proxy air volume based on fan operating parameters, and establishes a dual-cross-limit control mechanism between the proxy air volume and the coal feed rate; based on this, a predictive control optimization model incorporating dual-cross-limit control is constructed, and the optimal control sequence of the control quantities is obtained through a model predictive control solver, and the first control quantity in the optimal control sequence is written into the controller for execution.

This invention discloses an online method and system for estimating the braking clearance throughout the entire lifecycle of an EMB system, relating to the field of braking technology for EMB systems in autonomous vehicles. The invention includes: acquiring motor current and motor angle signals of the electromechanical braking system during the braking clamping phase; constructing a current-angle regression model based on a Legendre orthogonal basis based on the nonlinear relationship between the motor current and motor angle signals; performing online robust estimation of the parameter vector of the current-angle regression model using a weighted multi-forgetting factor recursive least squares algorithm combined with an adaptive M-estimator and a two-stage estimation strategy; and mapping the parameter estimates to braking clearance estimates. This invention achieves high-precision braking clearance estimation without additional sensors based solely on motor current and angle signals through online self-learning. It maintains excellent robustness and stability under complex operating conditions and long-term operation, making it suitable for engineering applications in EMB systems.

The application discloses a ground TT&C station fault diagnosis system and relates to the technical field of space TT&C.The application aims at the problems that the existing fault diagnosis of the ground TT&C station under the environment of low signal-to-noise ratio, multi-node concurrency and strong interference depends on fixed threshold, is difficult to depict the space-time correlation of faults and is highly sensitive to the quality of spectral data, etc., and the application is characterized in that: a plurality of monitoring branches are arranged before and after a plurality of key devices of a link, and multi-modal data such as spectrum, temperature, voltage and environmental parameters are collected, so that the diagnosis system no longer depends on single spectral information, and other observation quantities can be used to maintain the discrimination of the device state when the signal is seriously attenuated or interrupted for a short time; in cooperation with a data preprocessing module, the missing value compensation and targeted normalization or interval scaling are performed on the data from different sources, so that the characteristics of the same node at each time point are kept continuous and dimensionally unified, and the numerical stability of the training and reasoning process of the graph attention network is significantly improved.

The application discloses a kind of physical constraint under aero-magnetic data deep learning forward and inversion method and system. Including: constructing the forward network based on deep operator network DeepONet, the network adopts logarithm-linear dual space mechanism, to log resistivity profile and flight height as input, predicts log quadratic field;Inversion network is constructed, with the input of observed transient electromagnetic response and flight height, and the output of resistivity profile;When training, the forward network is pre-trained to convergence under data-driven loss and Maxwell equation physical constraint loss;Inversion network is trained under the joint supervision of its model space loss and physical data space loss, wherein the physical data space loss is obtained by comparing the re-synthesized response with the original observation after inputting the resistivity profile predicted by the inversion network into the frozen forward network.The application deeply integrates physical laws into data-driven models, and realizes the integrated efficient solution of aero-magnetic forward and inversion.

The application discloses a method for designing and controlling relative motion configuration of spacecraft formation in the Earth-Moon libration point orbit, and belongs to the technical field of spacecraft orbit dynamics and control. The method firstly constructs a double-level dynamics model composed of a circular restricted three-body problem model and a high-precision ephemeris model, and defines the orbit amplitude difference and phase difference as configuration parameters; then, according to different combinations of the orbit amplitude difference and phase difference, three types of natural relative motion configurations are set, periodic orbits are quickly generated under the circular restricted three-body problem model, and multiple turns are corrected by using the high-precision ephemeris model and two-stage multiple shooting; for the controlled tasks of fixed position, plane and space encirclement, a hierarchical constraint model is established, and a two-stage optimization strategy is adopted to solve the control pulse. The application realizes efficient design and stable control of the formation configuration in a complex dynamics environment, and is suitable for various libration point orbit tasks.

The application provides a plane constraint-based spectral confocal probe pose calibration method and device, and belongs to the field of precision measurement and instrument technology.The method comprises the following steps: firstly, at least three non-coplanar plane standard parts are measured by using a contact probe, and through coordinate conversion and fitting, equations of the standard planes in a machine coordinate system are accurately established; then, the same plane parts are measured by using a spectral confocal probe, and the obtained measurement point coordinates and distance values are combined with the known plane equations to construct a linear over-determined equation set about the probe pose parameters (including an optical axis direction vector and a space position vector); finally, the equation set is solved by using a least square method to obtain accurate pose parameters.The application converts a nonlinear problem into a linear solution, avoids iterative calculation, and significantly improves the calibration efficiency and accuracy.Meanwhile, the use of plane constraint allows the measurement points to be uniformly distributed, effectively reduces the equation set ill-conditioning, and enhances the robustness of the calibration process.

The invention discloses a target system for advanced planning and production scheduling (APS) and a unified construction method and an extension system thereof. By establishing a mapping relationship between business constraints and decision elements, standardizing a data structure and a management process of decision factors, and combining an operator target construction link with a template scene library, automatic construction and dynamic reconstruction of an optimization target are realized. In order to solve the problem that the business target cannot be satisfied, the invention provides a decision-making target switching mechanism and a constraint softening mechanism so as to generate an executable scheme which can be satisfied to the greatest extent. And meanwhile, weight management methods such as weight cutting, normalization, sensitive scanning and automatic optimization are provided, so that the numerical stability and interpretability of the target construction process are ensured. The system supports cloud, local and hybrid deployment, can improve solution robustness, business adaptability and decision efficiency, and promotes engineering landing and popularization of the APS in a manufacturing industry scene.

This invention discloses a joint module parameter identification method based on modulation function DREM and active excitation, belonging to the field of robot joint control technology. The method includes: constructing a linear regression model containing the electrical parameters to be identified; using multiple modulation functions with zero boundary conditions and linear independence to perform weighted integral transformations on the linear regression model, obtaining multiple integral algebraic equations without differential terms, and combining them to form an extended regression matrix; constructing a decoupled determinant based on the adjoint matrix of the extended regression matrix, and decoupling the extended regression matrix into multiple independent scalar equations; injecting a disturbance signal into the control loop of the permanent magnet synchronous motor when the amplitude of the decoupled determinant is lower than a preset excitation threshold; updating the corresponding electrical parameters to be identified based on each scalar equation and outputting the identification result. This method solves the problems of low parameter identification accuracy and slow convergence of joint modules under high noise and low excitation conditions, significantly improving the control performance of robot joints.

The invention relates to the technical field of large-scale structure space pose online compensation, and discloses an adjustment positioning system and method based on laser tracking, and the method comprises the steps: laying a plurality of laser tracking targets, and building an observation model with the pose and deformation separated; solving to obtain a rigid body posture estimation value and a deformation state estimation value; an executor instruction is updated, and a posture adjustment executor is driven to carry out posture adjustment; the die length of the deformation state estimation value is detected, and an unloading force balance fine adjustment process is triggered; judging whether the adjustment reaches the target precision or not; a laser tracking target is arranged and an observation model is introduced, measurement points collected by a laser tracker are modeled as superposition of rigid body poses and finite-dimensional deformation, rigid body rotation, rigid body translation and deformation modal coefficients are estimated, the poses and deformation can be separated from each other in the aspect of mechanism, and the measurement precision is improved. And the positioning precision and the installation and adjustment reliability of the high-precision optical installation and adjustment station are improved.

The invention relates to the technical field of remote sensing satellite ground data processing, in particular to a multi-probe star camera internal and external parameter joint calibration method, which comprises the following steps: constructing an initial light pointing model, and resolving initial attitude parameters; calculating a theoretical image space coordinate of a fixed star control point based on the initial attitude parameter, calculating an attitude parameter again by using the star point data after gross error elimination, and determining a relative installation relation initial value among the multi-probe star cameras; based on the angular distance constraint between star points in a single-frame image, constructing a single-probe internal parameter calibration model and a combined calibration model with internal parameters and relative installation relations as unknown numbers; the observation equation is weighted according to the weighting model, the internal and external parameters are updated based on the resolving result, iterative optimization is carried out until the convergence condition is met, the accurate internal and external parameters of the star camera are obtained, the influence of observation errors on parameter resolving is effectively restrained, and the calibration precision and the reliability of parameter estimation are further improved.

The present application belongs to the technical field of multi-agent cooperative control and path planning, and particularly relates to a multi-agent collision-free prediction optimization method based on smooth potential field and parallel ADMM. The method is based on the parallel ADMM architecture, and decouples the optimization problem into two sub-problems of individual dynamics and cooperative collision avoidance. At the individual level, the dual decomposition technique is used to convert the constrained optimization into a parallel solution of dual quadratic programming; at the cooperative level, a second-order differentiable smooth potential energy function is used to replace the mixed integer programming to handle the collision avoidance constraint. The present application reduces the computational complexity from exponential to polynomial, and significantly improves the real-time planning capability and robustness of large-scale multi-agent clusters in complex environments.

This invention provides a method and system for analyzing the surface shape changes of coatings on ultrathin crystal devices based on finite element analysis, belonging to the field of data processing technology. The method includes: calculating the displacement gradient tensor of subdomain elements to obtain entropy correction coefficients; correcting the amplitude of a uniformly distributed mechanical load based on the entropy correction coefficients to obtain a final uniformly distributed mechanical load; reloading the final uniformly distributed mechanical load into a numerically corrected configuration, repeating the solution and load correction process until the absolute difference of the entropy correction coefficients between two adjacent iterations is less than a preset tolerance, obtaining a final convergent potential field; and extracting the nodal displacement distribution on the substrate surface based on the final convergent potential field to obtain the surface shape change result. This invention can more accurately solve the displacement field and surface shape changes of ultrathin crystal devices after coating, effectively improving the convergence stability and numerical reliability of surface shape analysis.

This invention provides a method and system for reconstructing the outer contour function of a projectile's head shape based on machine vision, belonging to the field of machine vision image processing and automatic parameter calculation technology. First, the invention performs semantic segmentation on the frontal view image of the projectile's head shape to obtain a binary mask of the projectile target, and extracts and crops the outer contour of the head shape segment. Second, through coordinate axis self-calibration and attitude alignment, the standard attitude coordinates of the projectile's head shape outer contour are obtained. Then, in the local coordinate system, geometric constraint feature points are extracted to obtain the endpoints, pixel areas, and single-point coordinates of the projectile's head shape outer contour. Third, a two-parameter head shape outer contour shape function satisfying endpoint constraints is constructed, and the shape parameters are solved using area constraints and single-point constraints to obtain the analytical expression of the head shape outer contour. Finally, the outer contour function and its derivative are substituted into the head shape factor integral formula to achieve automatic calculation of the head shape factor.

This invention discloses a high-precision 3D edge reconstruction method for bevel cutting. The method first acquires the original point cloud and grayscale image of the workpiece using a binocular vision system; then, it uses the filtered clean point cloud to fit the plane equation of the workpiece surface as a geometric constraint; next, it performs adaptive feature enhancement on the grayscale image to extract high-precision sub-pixel 2D edges; finally, it combines the plane equation and the 2D edges, calculates the 3D coordinates of the edges using a ray intersection model, and generates the robot cutting trajectory. This invention effectively solves the problems of point cloud loss and distortion caused by edge burrs, defects, and reflections, achieving sub-millimeter-level edge reconstruction and significantly improving the consistency of bevel cutting edges and trajectory accuracy without manual intervention.

The invention discloses a phase field control equation numerical solution method. The method comprises the following steps: S1, establishing a phase field control equation representing a basic physical process; s2, deducing a weak form of the phase field control equation; s3, dispersing a displacement field and a phase field in the phase field control equation by adopting a shape function to respectively obtain domain weak forms of a displacement field equation and a phase field equation; s4, creating a user phase field model through an interactive interface of the PDE module builder; s5, after vector function discretization is carried out on the displacement field equation and the phase field equation by adopting a PDE module, an associated coefficient field is specified in the module; and S6, solving the numerical model by strictly applying boundary conditions and initialization parameters. According to the numerical solution method for the phase field control equation, through innovative algorithm design, the calculation efficiency and the numerical stability are remarkably improved.

The application discloses a multi-strategy unmanned aerial vehicle rapid obstacle avoidance path planning method based on dynamic ellipsoid sampling, which comprises the following steps: constructing an ellipsoid according to the starting point and the ending point of the unmanned aerial vehicle path planning, mapping a sampling point to the ellipsoid space to obtain a sampling point in the ellipsoid, and dynamically adjusting ellipsoid parameters through cyclic sampling to obtain an initial planning path and path nodes, which can focus on an effective area and improve sampling efficiency; a multi-strategy expansion mechanism is used to optimize the initial planning path nodes, and the convergence speed and obstacle avoidance ability are improved; potential parent nodes meeting the feasibility condition are searched in the neighborhood of the optimized path nodes, and the node with the minimum path cost is selected as a new parent node, and the new parent node is used to update the optimized planning path; a three-stage path smoothing strategy is used to smooth the updated optimized planning path, and an unmanned aerial vehicle planning path is obtained, so that the path feasibility and safety are ensured, and the path smoothness is improved.

This invention discloses a method and apparatus for evaluating the load-bearing capacity of the anchorage section of a guy wire, applied in the field of line stress detection technology. It aims to improve the comprehensiveness of stress monitoring within enclosed structures such as the anchorage section of a guy wire on towers, and enhance the comprehensive assessment capability of structural safety under extreme conditions. The method involves collecting the center wavelength data of a fiber optic grating on the target guy wire, calculating the mean strain sequence of the target guy wire based on the center wavelength data and fiber optic grating parameters, and then inverting the axial force, bending moment, and shear force of the target guy wire based on the mean strain sequence. Finally, the load-bearing capacity of the target guy wire is evaluated based on the axial force, bending moment, shear force, and a preset standard load-bearing range to obtain the evaluation result.

The application discloses a cable relaxation spectrum identification method and system based on forward and backward dynamic modal decomposition, relates to the field of high voltage and insulation technology, and aims to solve the technical problems that the branch number of the extended Debye model cannot be automatically determined in the prior art, and the relaxation parameter identification is easily disturbed by false modes under low signal-to-noise ratio, thereby causing the identification result to not conform to the physical attenuation characteristic. The cable relaxation spectrum identification method based on forward and backward dynamic modal decomposition comprises the following steps: acquiring a discrete sequence of a cable insulation depolarization current, constructing a Hankel matrix, and generating a first snapshot matrix and a second snapshot matrix; constructing an augmented matrix, and determining an effective rank order; constructing a projection matrix, and acquiring a first projection snapshot matrix and a second projection snapshot matrix; estimating a discrete attenuation eigenvalue set; acquiring effective relaxation components and corresponding relaxation time constants; solving current amplitudes corresponding to the relaxation components, and outputting a relaxation spectrum containing the relaxation time constants and the current amplitudes.

The invention provides a Viterbi decoding method, a medium and a computer program product for gene sequencing. The method comprises the following steps: acquiring a transmission fractional matrix generated by a recurrent neural network; backward traversal calculation is executed, the backward probability for each time step, batch and state is iteratively calculated from the tail end to the starting end of the base sequence, and the backward probability represents the expected cumulative score from the corresponding state to the tail end of the sequence for the corresponding time step and batch; generating a guiding score matrix based on the emission score matrix and the backward probability, wherein the guiding score matrix contains guiding scores for each time step, batch, state and base type index; and performing forward Viterbi decoding and backtracking by using the guide fractional matrix to obtain a decoded base sequence.

The river network rain and pollution regulation facility hydrodynamic and associated process simulation method disclosed by the application collects basic data of a research area, and constructs a river network numerical model based on the data, sets corresponding regulation nodes and rules in the river network numerical model, and completes model initialization; solves river section water depth, flow and pollutant concentration through the model and updates related indexes, calculates node flow and pollutant amount, obtains node minimum limit step, and calculates flow discharge according to the characteristics of the hydraulic facility, replaces the original numerical flux, strictly conserves water quantity conservation and updates upstream and downstream water levels of the facility; then the minimum time step of the pipe section is obtained according to the CFL condition, and the pipe section hydraulic elements and node water depth are updated as the model calculation step, and after the calculation is completed, the water flow simulation results of the river network river section and the regulation facility are output.

The application relates to a two-way coupling method and system of a multi-scale heterogeneous grid land surface hydrological model, which comprises the following steps: S1, multi-source data collection and preprocessing: collecting and preprocessing multi-source data required for coupling simulation; S2, model and coupler initialization: initializing a land surface process model, a hydrological model and an OASIS3-MCT coupler; embedding OASIS coupling interfaces in the two models respectively, and completing the definition of coupling grid information, task partition mode and a coupling variable list; S3, grid interpolation and time synchronization: realizing cross-model transmission of coupling variables between CLM5.0 and SHUD; S4, coupling simulation under a main time loop; S5, checking of simulation results, including energy balance checking and convergence checking; and S6, ending simulation and releasing memory resources. The application effectively solves the problems of model compatibility and data exchange under heterogeneous programming languages, different grid structures and parallel communication mechanisms, and improves the coupling calculation efficiency and simulation accuracy.

The application discloses a laser calibration method and device, which is applied to the technical field of laser processing and comprises the following steps: projecting a laser beam on a calibration plate according to a preset circular array calibration pattern through an electric laser galvanometer unit, so as to generate a calibration pattern on the calibration plate and record a galvanometer coordinate set corresponding to each feature point in the calibration pattern; collecting the calibration pattern generated on the calibration plate to obtain a calibration image; processing the calibration image to extract an image coordinate set corresponding to each feature point in the calibration image; constructing a transformation matrix between the galvanometer coordinate set and the image coordinate set; and converting the coordinates in the galvanometer coordinate system into corresponding coordinates in the image coordinate system based on the transformation matrix, so as to complete laser calibration. The application solves the transformation matrix by acquiring the calibration pattern and extracting the center feature point, and the calibration of the galvanometer and the image coordinate system can be completed without the aid of external standard calibration equipment, so that the operation process is effectively simplified and the hardware cost is reduced.

The application provides a kind of spaceborne conical scanning Doppler radar three-dimensional wind field inversion method and device, the method comprises: the radar observation strip area is divided into multiple sub-blocks, and there is area overlap between adjacent sub-blocks, and the horizontal wind field of each height layer is parameterized in each sub-block with piecewise continuity variation assumption;Variational method is used to obtain the optimal horizontal wind field parameter of each height layer in each sub-block, and the horizontal wind field in each sub-block is determined according to the optimal horizontal wind field parameter, the horizontal wind field of the corresponding position of each sub-block in the overlapping area is linearly weighted and fused to obtain the final horizontal wind field;The horizontal divergence is calculated according to the optimal horizontal wind field parameter of each height layer in each sub-block, and the vertical wind field is obtained by integrating the horizontal divergence in the height direction using the atmospheric mass conservation equation, and the vertical wind field of the corresponding position of each sub-block in the overlapping area is linearly weighted and fused to obtain the final vertical wind field.The application realizes the continuous and robust three-dimensional wind field inversion of spaceborne conical scanning Doppler radar.

The invention discloses an underground water reactive solute transport prediction method and model based on a physics-graph neural network. The method comprises the following steps: inputting directed graph structure data of a target groundwater chemical system into a parameterized graph neural network for prediction to obtain a reaction rate parameter and pH and pe residual results of a microbial reaction of the target groundwater chemical system at a tth time step; inputting the reaction rate parameter into the dynamic physical network to predict the reactive solute concentration of the (t + 1) th time step; and inputting the residual results of the concentration, the pH value and the pe into a residual correction network for correction to obtain the reactive solute concentration, the pH value and the pe value of the target groundwater chemical system at the (t + 1) th time step. According to the method and the model, efficient and high-precision prediction results are realized, and the method and the model are applicable to a complex biogeochemical system.

The invention discloses a dominant broadband oscillation order reduction method suitable for a network tracking / constructing type hybrid wind power plant. The method comprises the following steps: firstly, establishing a full-order small-signal model of the hybrid wind power plant, and identifying a dominant broadband oscillation mode in combination with an energy contribution degree and a controllable observability criterion; secondly, state variable division and order reduction modeling are carried out based on the singular perturbation principle, and the calculation complexity is reduced while the dominant modal precision is kept; and finally, model simplification and dynamic characteristic consistency are realized through module interface matching and stability verification. According to the method, the reduced-order model of the hybrid wind power plant can be quickly obtained under the condition that main dynamic characteristics are not influenced, and reliable technical support is provided for broadband oscillation analysis and control optimization of a power system.