20 results about "Nonlinear parameters" patented technology

The present invention discloses a method for identifying nonlinear parameters of structural clearances. First, a mathematical model of the structural clearance nonlinear system is established; then, the frequency response function of the system under sinusoidal sweep excitation is obtained through the input-output response of the system; in the frequency response function, a pair of symmetric displacement points exist at any displacement response amplitude to define the same displacement frequency response function. By defining the real and imaginary parts of the displacement frequency response function through the symmetric displacement FRF points at each given displacement response amplitude, the natural frequency of the system related to the displacement response amplitude can be obtained; then, the expression of the nonlinear equivalent stiffness of the system is extracted through the simulation analysis of the model, and the equivalent stiffness curve of the system is further obtained through the model simulation data; finally, based on the particle swarm algorithm, the clearance characteristic parameters are obtained by curve fitting according to the equivalent stiffness expression obtained by integration and the equivalent stiffness curve obtained by model simulation; the present invention can identify the clearance nonlinear parameters more quickly and accurately globally.

The application is a method for the influence of dislocation dipole defects in aluminum matrix on acoustic parameters, belonging to the technical field of discrete solution, and provides a new molecular dynamics simulation method for researching the changes of ultrasonic velocity, acoustic attenuation and acoustic nonlinear parameters based on two dislocation dipole structures, specifically, the types and quantities of dislocation dipoles in the aluminum matrix are controlled, the atomic scale acoustic simulation is carried out on the dislocation dipole models of different types and quantities by using the phase inversion technology, the cross correlation method is used to extract the sound velocity, the Hilbert transform method is used to extract the sound attenuation, and the FFT method is used to extract the acoustic nonlinear parameters for the four-phase signals, so as to realize the precise extraction of acoustic parameters. Based on the fitting relationship between the three acoustic parameters and the dislocation defects, the contribution of the dislocation defects to the acoustic parameters is determined, and the prediction from the acoustic parameters to the defect characteristics is realized.

The application discloses a point cloud rendering method and system, and relates to the technical field of computer graphics, and comprises the following steps: acquiring point cloud data of a detected object; S2, dynamically dividing a three-dimensional space into multiple rendering levels based on the real-time distance from the acquired point cloud data to a current observation point; based on each rendering level, respectively establishing a nonlinear smooth continuous function mapping relationship between rendering sampling probability and the observation distance of a rendering point radius, and respectively inputting a preset representative observation distance at each layer to obtain the rendering parameters of each layer; and applying the corresponding rendering parameters of the point cloud of different rendering levels to perform differentiated rendering operations. Advantageous effects: the hierarchical mechanism provides a structured framework for subsequent nonlinear parameter mapping, so that the adjustment of the rendering parameters can be based on an ordered spatial division closely related to visual perception, which is a prerequisite for the intellectualization of the whole method.

This invention discloses a safety assessment system and method for pressure-bearing components based on nonlinear ultrasound, belonging to the field of component safety assessment technology. The invention controls a robotic arm to drive an automatic probe to acquire nonlinear signals; establishes a mapping benchmark library and calibrates the background nonlinear threshold; divides the detection area of ​​the pressure-bearing component under test into a grid, and acquires the original field detection signal corresponding to each grid unit; removes nonlinear interference from each original field detection signal and calculates effective nonlinear parameters; based on the effective nonlinear parameters and the background nonlinear threshold, filters out abnormal candidate regions; for all abnormal candidate regions, inversely calculates the equivalent emission source parameters of the abnormal nonlinear signals; based on the three-dimensional spatial coordinates of the equivalent emission source parameters, determines the abnormal location region and outputs the location characteristics of the abnormal location region; trains a safety assessment model, inputs the location characteristics into the safety assessment model, and calculates the safety assessment result of the pressure-bearing component.

The present application relates to the technical field of permanent magnet synchronous motor control, and particularly relates to an adaptive method for actively feeding forward and compensating cogging torque of super-multipole permanent magnet synchronous motor, which is as follows: a cogging torque feedforward compensation model is established, and the amplitude-phase nonlinear parameters are converted into linear weight coefficient form through triangular orthogonal decomposition; secondly, the AC component of the q-axis voltage output by the current PI regulator is extracted as a compensation residual error signal, the weight coefficient is updated on-line and iteratively using the normalized least mean square algorithm, and adaptive tracking of the cogging torque change caused by temperature drift and mechanical wear is realized; finally, combined with a dual-redundant position feedback system, a double-channel independent weight coefficient maintenance, cross-checking and seamless fault switching mechanism is established. The present application can reduce torque ripple under low-speed working conditions, improve the low-speed stability and control accuracy of super-multipole permanent magnet synchronous motor, and meet the functional safety requirements of aviation-grade electric drive systems.

The application discloses a kind of node inertia identification method, system, equipment and medium of power system, it is related to power system inertia identification technical field, including after detecting load step disturbance, the active power and frequency data of target node are preprocessed, and fixed disturbance window before and adjustable disturbance window after are respectively set, power and frequency sequence are intercepted, dynamic parameterization model is established and discrete domain transfer relationship is obtained by nonlinear parameter estimation iterative optimization model parameter, whether model is reduced to first order is judged using fitting degree index and is re-identified, and discrete domain transfer relationship is converted into continuous domain transfer relationship, the order reduction processing is executed to second-order model, inertia time constant and damping coefficient are calculated by applying step excitation, re-optimization process, until meeting the condition output node inertia.The present application cooperates nonlinear parameter solution and adaptive window searching, while considering identification speed, significantly improves the accuracy and robustness of node inertia identification.

This application relates to the field of optical fiber communication technology, and discloses a method and electronic device for optical fiber link anomaly analysis. The method includes: acquiring a modulated optical signal from the transmitting end of the optical fiber link and an actual sampled signal from the receiving end of the optical fiber link; generating an actual observation signal based on the actual sampled signal; constructing a differentiable physical model; inputting the modulated optical signal into the differentiable physical model to generate a predicted observation signal; iteratively optimizing the distribution of fiber dispersion parameters and longitudinal nonlinear parameters in the differentiable physical model based on the predicted observation signal and the actual observation signal until the differentiable physical model converges; and performing anomaly analysis on the optical fiber link based on the converged longitudinal nonlinear parameter distribution. This application can improve the accuracy of optical fiber link anomaly analysis.

The application discloses a kind of based on large-capacity backbone optical communication link delay equalization method of wavelength division multiplexing, belong to optical communication technical field, comprising the following steps: S1, collection WDM backbone link on optical domain, electric domain, environment and nonlinear parameter, after pre-processing, upload to control center;S2, construct delay prediction model, utilize the data of collection and train model, the delay variation trend and delay difference of future each wavelength channel are predicted in real time, if the delay difference of prediction exceeds service threshold then trigger equalization decision;S3, with minimum delay difference, reduce energy consumption, satisfy service demand as goal, generate optical domain-electric domain-cross node collaborative equalization strategy;S4, according to equalization strategy, respectively carry out optical domain equalization, electric domain equalization and cross node collaborative scheduling;S5, carry out equalization effect feedback and adaptive optimization.The application has significantly improved equalization precision and reduced system energy consumption, and has strong dynamic adaptability.

This invention discloses a wind power generation prediction method based on a variable-priority adaptive grey model. The method involves collecting annual wind power generation data for a target area and establishing an original sequence; introducing weight parameters and an adaptive variable weight function to construct a variable-priority accumulation operator; calculating a variable-priority accumulation sequence using the original sequence and the variable-priority accumulation operator; introducing the variable-priority accumulation sequence and a double nonlinear term to improve the grey discrete model, thus constructing a variable-priority adaptive grey discrete model; optimizing the nonlinear parameters of the model using a hybrid algorithm of social spider and differential evolution to obtain optimal nonlinear parameter values; and then solving the parameters of the model's time response equation using the least squares method to obtain the optimal model; finally, using the optimal model to predict future wind power generation. The introduction of a variable-priority accumulation operator adaptively adjusts the data priority to reduce the impact of uncertainty in new wind power data, thereby improving the prediction accuracy of wind power generation.

The embodiment of the application discloses a steel wire rope defect detection method and system based on feature fusion and dimension reduction optimization, which comprises the following steps: acquiring a double-field metal magnetic memory signal of a steel wire rope; constructing a defect response term and a baseline drift term for the double-field metal magnetic memory signal based on a composite model construction method to obtain a metal magnetic memory signal analysis model; the parameters in each metal magnetic memory signal analysis model include nonlinear parameters and linear parameters; the value of the nonlinear parameters is searched iteratively based on an optimization algorithm; based on the value of the nonlinear parameters, the corresponding metal magnetic memory signal analysis model is characterized as a corresponding base matrix; the base matrix and the metal magnetic memory signal component are subjected to matrix pseudo-inverse operation to obtain the linear parameter estimation value corresponding to the value of each nonlinear parameter; based on a preset joint fitness function, the value of each nonlinear parameter and the corresponding linear parameter estimation value are evaluated to obtain optimal nonlinear parameter values and optimal linear parameter values, and defect information is output.

This disclosure provides a temperature sensor and a temperature calibration method, which can be applied in the field of sensing technology. The method includes: a temperature sensing circuit for determining a nonlinear parameter based on a third adjustable parameter and a temperature coefficient based on a first adjustable parameter; a signal conditioning circuit for determining a zero-degree output parameter based on a second adjustable parameter; and a temperature sensor for determining a calibration output curve based on the nonlinear parameter, the temperature coefficient, and the zero-degree output parameter; wherein the second and third adjustable parameter signals are parameters of the signal conditioning circuit, the first adjustable parameter is a parameter of the temperature sensing circuit, and the calibration output curve is an output curve that is linearly related to temperature.

This invention discloses an automatic optimization method for force field parameters of a biomembrane mesoscopic model under multi-system joint constraints, belonging to the field of computational physics and mesoscopic simulation technology. The method includes: constructing a parallel co-simulation system; implementing parameter decoupling and hierarchical mapping strategies on the parallel co-simulation system, and discretizing the global force field parameter set; initializing a particle swarm optimization algorithm; simultaneously launching the LAMMPS simulation engine using the MPI parallel mechanism for each set of force field parameters in the swarm to calculate the parallel co-simulation system; post-processing the obtained simulation trajectory to extract macroscopic physical properties and compute physical constraint indices; constructing a loss function; iteratively updating, and finally outputting the obtained optimal force field parameter set. This invention constructs a mesoscopic force field without relying on all-atom simulation, avoids non-physical solutions in a high-dimensional nonlinear parameter space, and ensures the portability of the obtained parameters across different physical systems.

This invention discloses a comprehensive microwave chip wafer-level performance testing device and method, belonging to the field of microwave chip testing technology. The device includes a signal source, receiver, coupler, circulator, switch, matching unit, chuck, etc., forming a specialized comprehensive microwave chip wafer-level performance testing system. The testing method includes comprehensive measurements of scattering parameters and derived coefficients, distortion parameters, power parameters, spectral parameters, pulse parameters, noise parameters, and nonlinear parameters. This invention effectively improves testing accuracy and speed, thus solving the challenge of high-precision and high-efficiency testing of microwave chips. A single testing device can fully evaluate testing capabilities, significantly reducing construction costs.

The present application relates to the technical field of non-destructive characterization of composite material interface, and provides a method for characterizing fracture toughness of aircraft composite bonding structure based on nonlinear guided waves, which comprises applying nonlinear guided wave excitation to the bonding structure of the aircraft composite skin and shell to be tested, collecting the first-arriving guided wave signals propagating along the bonding interface in each bonding sample to be tested; performing frequency domain analysis on the first-arriving guided wave signals on each propagation path, extracting the amplitudes of the fundamental frequency component, the second harmonic component and the third harmonic component, calculating the corresponding nonlinear parameters and the normalized nonlinear parameters; solving the corresponding interface evolution index by using the constructed bonding interface fracture toughness characterization model; converting the obtained interface evolution index into interface fracture toughness according to the mapping relationship between the interface evolution index and the type I interface fracture toughness established by experiments, and realizing the non-destructive fracture toughness characterization of the bonding sample to be tested.

An optimization method, system, device, and storage medium for an OPC model are disclosed. The OPC model includes nonlinear parameters. The optimization method includes: performing a first initialization process on the nonlinear parameters to determine a first search range; based on the first search range, performing a first search process on the nonlinear parameters using a global search algorithm to generate multiple first candidate values ​​corresponding to each nonlinear parameter; setting a second search range based on the multiple first candidate values, wherein the second search range is smaller than the first search range; and performing a second search process on the nonlinear parameters using a local search algorithm based on the second search range to obtain final candidate values. This invention improves the optimization effect of the OPC model, enhancing its accuracy and reliability.

This invention relates to the field of underwater weld technology and discloses a method and system for forward modeling of nonlinear ultrasonic scattering in the early stage of underwater welds. The method includes: obtaining material nonlinear parameters based on the ratio of second harmonic to fundamental wave amplitude; obtaining interface contact nonlinear parameters through the second harmonic amplitude in the reflected wave from the crack interface; establishing water-solid interface propagation conditions and constructing a sound velocity model; combining the sound pressure superposition relationship under multipath propagation and array excitation conditions to obtain the total fundamental wave sound pressure at any receiving point within the weld; and constructing a unified nonlinear ultrasonic forward scattering model by introducing equivalent local nonlinear parameters for unified characterization. This invention, by constructing a unified characterization model of material nonlinearity and contact acoustic nonlinearity, and combining the water-solid coupling propagation mechanism with Green's function forward modeling, can improve the completeness of the description of nonlinear ultrasonic scattering mechanisms and the accuracy and stability of the quantitative characterization of early-stage micro-damage in underwater welds.

This invention relates to an adaptive control method, device, medium, and equipment for robotic arm bone grinding, comprising: constructing a hierarchical model reference adaptive control framework based on the strong nonlinearity, parameter uncertainty, and contact stiffness path changes in bone grinding, through equivalent contact modeling at the object modeling layer and constraint-driven performance index design at the reference model layer; constructing an adaptive admittance controller with online adjustment of admittance parameters based on the requirements of force-position coordination and safe shutdown, through force-position hybrid control and an adaptive update law with projection constraints, to achieve smooth force-position transition during bone layer switching and automatic deceleration and shutdown of cancellous bone segments; proving the uniform boundedness of the closed-loop system based on Lyapunov stability theory, and verifying the effectiveness and robustness of the control strategy through cross-cortical-cancellous bone layer simulation. This invention can achieve force-position coordinated compliant grinding under unknown bone tissue conditions, ensuring surgical safety and operational continuity.

This invention belongs to the field of quantum communication technology and discloses a CV-QKD parameter optimization method and system adapted to actual channels. The method constructs a dual PSO-BP network model based on actual channel operating data. First, it collects operating data on code rate and key rate to obtain the first PSO-BP network model, establishes a mapping relationship between the two, and quickly finds the optimal code rate and maximum key rate. Then, based on the optimal code rate, it collects operating data on the number of decoding iterations and key throughput to obtain the second PSO-BP network model, and determines the optimal number of decoding iterations and the corresponding maximum key throughput through the mapping relationship. This method relies on machine learning models to avoid the optimization problem of nonlinear parameter correlation, reduces the computational complexity of key rate and throughput, improves parameter optimization efficiency, and can dynamically adapt to changes in actual operating conditions such as channel loss and environmental noise, effectively improving the key rate, key throughput, and transmission distance of the CV-QKD system.

The application discloses a motor nonlinear parameter modeling method based on a hybrid active learning sampling strategy. First, an unlabeled working condition set and a labeled working condition set are constructed, and a labeled sample set is obtained based on the labeled working condition set, and an initial training is performed on a data-driven model for modeling nonlinear parameters based on the labeled sample set. Second, based on two independently running hybrid active learning sampling strategies, working conditions with higher information value are selected from the unlabeled working condition set to form a selected working condition set, and a new sample set is formed through experimental calibration. Finally, the selected working condition set is removed from the unlabeled working condition set of the last round, and the new sample set is supplemented in the labeled sample set of the last round, so that the unlabeled working condition set and the labeled sample set of the current round are updated, and the data-driven model is incrementally trained based on the updated labeled sample set, and the iteration is performed until the convergence condition is met. The method is suitable for the application fields of motor modeling and optimal control.

The application provides a camera distortion correction method based on a spectral correction iterative LM algorithm, and belongs to the technical field of distortion correction. In view of the fact that in the existing nonlinear distortion correction model solving process, the nonlinear parameter estimation is not accurate, thereby directly affecting the correction result, the application innovatively provides a novel camera distortion correction method based on the spectral correction iterative LM algorithm. Specifically, a nonlinear function model of a camera imaging system is constructed according to a distortion correction model, and an observation value vector is obtained; an error equation of a nonlinear least square problem is constructed by using a Taylor formula, an iterative formula of a to-be-estimated parameter of the nonlinear least square problem is constructed according to a spectral correction iteration method; spectral correction estimation is calculated, an actual-to-estimated drop ratio is calculated, and the parameter estimation value of the secondary iteration is updated; and a judgment threshold is set, and when the convergence condition is met, the optimal parameter estimation value is output.