10 results about "Non linear wave" patented technology

The application discloses a nonlinear Lamb wave excitation deviation evaluation method and system under dispersion constraint, belongs to the technical field of ultrasonic nondestructive testing and structural health monitoring, and is based on a Rayleigh-Lamb frequency equation and a second-order perturbation theory to construct a second harmonic displacement field model, divides a phase velocity matching mode pair into an intersection type, a longitudinal wave type and a cutoff type; the contraction law of a propagation distance and a mode order on an excitation window is quantitatively analyzed, an excitation tolerance coefficient and a relative gain coefficient are introduced, a two-dimensional quantitative evaluation system of mode pairs is established, three typical mode pairs are divided and are adapted to different detection working conditions, and an aluminum alloy sheet experiment is completed to verify the application. The application adopts the above-mentioned nonlinear Lamb wave excitation deviation evaluation method under dispersion constraint, establishes a standardized mode evaluation system, and significantly improves detection sensitivity and engineering reliability.

The application discloses an effective wave height double-stage space-time prediction method and system based on diffusion residual correction, relates to the technical field of sea wave prediction, and inputs historical effective wave height data and corresponding historical wind field data into an effective wave height space-time prediction model for processing to obtain a preliminary effective wave height prediction result, and then inputs the preliminary effective wave height prediction result, the historical effective wave height data and synchronous forecast wind field data into a residual correction module based on a diffusion model to compensate for the preliminary prediction error and obtain a final effective wave height prediction result. The diffusion model based on the EDM architecture is innovatively introduced to finely reconstruct the prediction residual, the basic prediction field, the synchronous wind field dynamic factor and the prediction time limit are taken as multi-dimensional physical strong conditions to inject the diffusion generation process, the application can deterministically restore the high-frequency texture details and nonlinear wave components missed by the first-stage model, to a certain extent, the application can relieve the long-term deviation accumulation, improve the prediction quality in high wave areas and improve the prediction stability.

This invention discloses a nonlinear Lamb wave detection method for micro-damage in plate structures based on a flexible sensor array, belonging to the field of nondestructive testing technology. The method includes: generating a sinusoidal modulated excitation signal using a Hanning window; extracting nonlinear characteristic parameters reflecting micro-damage in the plate structure from the preprocessed signal using time-frequency analysis and empirical mode decomposition algorithms; generating a fused damage probability map based on compressed sensing theory and the extracted nonlinear characteristic parameters; constructing a damage distribution profile in the thickness direction by analyzing the penetration depth differences of Lamb waves at different frequencies; and automatically quantifying and analyzing the identified damage areas to obtain the damage detection results. This invention aims to achieve early identification and precise localization of micro-damage in plate structures, effectively overcoming the shortcomings of low sensitivity and inaccurate localization in traditional detection methods, and significantly improving detection accuracy, efficiency, and automation.

Systems and methods for generating a phase-resolved ocean wave forecast with ensemble based data assimilation are disclosed. An example method includes receiving radar data corresponding to an ocean surface, and determining a surface elevation and a surface potential of a portion of the ocean surface. The example method also includes generating an ensemble of perturbed ocean surface data, and applying a phase-resolved nonlinear wave model to the ensemble of perturbed ocean surface data to generate a set of forecast ocean surface data. The example method also includes receiving a subsequent set of radar data corresponding to the ocean surface, and determining a subsequent surface elevation and surface potential of the portion of the ocean surface. The example method also includes combining, by applying an ensemble Kalman filter, the set of forecast ocean surface data with the subsequent surface elevation and surface potential to generate a phase-resolved ocean wave forecast.

This invention relates to an experimental apparatus and method for simulating ship motion under severe sea conditions, belonging to the field of ship wave load testing technology. It addresses the problem that existing severe sea condition wave load testing technologies are insufficient in simulating realistic waves under actual sea conditions, such as high wave heights, distorted waves, and breaking waves. The wave-generating system includes a wave-generating plate located at one end of a water tank and swinging along the length of the tank, and a driving component for driving the wave-generating plate's swing. The nonlinear wave generation system includes a wave-generating rod and several jet pipes. The wave-generating rod is arranged along the width of the water tank and slidably set along the height of the water tank via a height adjustment component. The jet pipes are all located at the bottom of the water tank. This invention enables the simulation of the water-air mixture flow field and accurate measurement of loads in distorted and nonlinear waves under severe sea conditions. It allows for a wide variety of experimental types and diverse functions, and can replace the expensive and costly towing tanks used for general ship models.

The application provides a gas concentration detection method and device, terminal equipment and medium, comprising controlling a laser to output a laser signal covering a characteristic absorption spectral line of a to-be-detected gas, and converting the laser signal into an original electric signal after passing through the to-be-detected gas via a standard-free light path; demodulating the original electric signal to extract first-order and second-order harmonic signals, and calculating a multi-dimensional harmonic characteristic ratio; obtaining temperature and pressure, introducing a spectral line broadening correction coefficient to construct a physical temperature and pressure model, and correcting the multi-dimensional harmonic characteristic ratio; extracting a waveform feature of a non-absorption reference region, performing nonlinear waveform distortion self-calibration on the corrected harmonic characteristic ratio, and obtaining a final harmonic characteristic ratio; establishing a theoretical mapping relationship between the final harmonic characteristic ratio and a to-be-detected gas concentration based on the Lambert-Beer law, and substituting the final harmonic characteristic into the to-be-detected gas to obtain a gas concentration detection result of the to-be-detected gas. The application can improve the accuracy and robustness of gas concentration detection.

This invention provides a method and apparatus for nonlinear wave field reconstruction and prediction based on lidar. The method involves scanning the wave field with lidar to obtain the coordinates of sampling points, setting a cost function, and solving the cost function with the sampling point coordinates to obtain the wave surface expression. This improves the efficiency of wave surface reconstruction while ensuring reconstruction accuracy. Based on the wave surface expression, a predictable region is obtained. An objective equation is set to iteratively solve the wave surface expression to obtain the corresponding discrete values ​​of velocity potential, avoiding the Jacobian matrix generated during Newton iteration, thus improving the efficiency of velocity potential solution. Finally, based on the wave surface expression and the corresponding discrete values ​​of velocity potential, the wave surface condition at subsequent time points is predicted, and the prediction results within the predictable region are taken as the valid prediction results.

The application provides an iterative quantitative imaging method based on a nonlinear Lamb wave mixing sound field, and steps are as follows: a finite element model of a metal plate containing a complex mode early damage is established; a mixing fundamental wave mode pair and a working frequency are determined; mixing sound field signals in a non-damage state and a damage state are obtained through finite element simulation, and a frequency domain sound field matrix of a difference frequency, a sum frequency and a fundamental frequency is extracted; ray tomography positioning representation is carried out by using the frequency domain sound field matrix of the difference frequency, first imaging is realized, the first imaging is fused with the fundamental frequency sound field feature to strengthen positioning representation, and an initial velocity model of iterative quantitative imaging is established; an offline training data set is constructed, a nonlinear mapping model of sound field changes and model changes is learned based on a conjugate gradient method, online inversion based on the optimal nonlinear mapping model is carried out, and second imaging is realized; and the application extracts the sum frequency and the difference frequency component, keeps high sensitivity of the nonlinear ultrasonic to microscopic and mesoscopic damage, and significantly improves detection reliability.

The application discloses a kind of electric vehicle charging load prediction method and system based on space-time frequency multi-domain state space model.The method first uses discrete wavelet transform to decompose non-stationary load data into orthogonal low-frequency trend component and high-frequency characteristic component, the frequency domain component is fused with time embedding feature and space embedding feature, realize the multi-dimensional feature extraction of original charging load sequence;Subsequently, the extracted features are input into the hierarchical coding structure, and the core uses parallel bidirectional Mamba processing flow to synchronously capture the forward and backward long-term time dependence of the sequence.Thirdly, the encoded latent variable is input into the symmetric multi-layer decoder, the multi-scale information from the encoder is integrated using the skip connection, and the recursive feature recovery and refinement are performed through the bidirectional Mamba flow.Finally, the high-precision prediction result is output through the linear mapping layer.The application uses a linear computational complexity state space model to solve the problem of excessive computational overhead when the traditional Transformer model processes long sequences, as well as the non-linear, volatility and long-distance dependence problems that traditional models cannot handle.Experiments show that the method improves the prediction accuracy while greatly reducing the inference power consumption, and the system is suitable for deployment on the power grid scheduling terminal with lightweight requirements, helping to balance and schedule the load in the power network.

The application discloses a simulation generation method and device for near-shore strong nonlinear waves and a terminal, and relates to the technical field of ocean engineering, in particular to a simulation generation method for near-shore strong nonlinear waves. The method comprises the following steps: acquiring sea surface height data of a tsunami wave at a certain position; inputting the sea surface height data into a wave speed variation and water depth variation relationship model, wherein the wave speed variation and water depth variation relationship model outputs wave flow speed; and obtaining a tsunami wave based on the sea surface height data and the wave flow speed. Compared with the prior art, the application can accurately generate strong nonlinear waves in a computational fluid dynamics model, fills the gap of the model method in this aspect, lays a foundation for the research on strong nonlinear waves, such as extreme storm surges and tsunami waves, and engineering effects thereof, and thus can more accurately understand, simulate and quantify the engineering effects of extreme wave disasters.