13 results about "Spline wavelet" patented technology

The invention discloses a method for analyzing time-frequency characteristics of collision vibration by using a segmented B-spline wavelet collocation method, which comprises the following steps of: (1) establishing a dynamic equation for wavelet discretization, discretizing a dynamic control equation of a collision-vibrator system by using a 4-order B-spline wavelet basis function, and establishing a nonlinear algebraic equation set about a wavelet coefficient; (2) carrying out segmented iterative solution on the time domain, dividing the whole time domain into a plurality of sub-time periods which are connected in sequence, and carrying out iterative solution on the nonlinear algebraic equation set in each sub-time period to obtain a global wavelet coefficient; and (3) analyzing the time-frequency characteristics, and directly calculating energy distribution based on the wavelet coefficient to realize time-frequency joint characterization. The invention aims to provide a method which can fuse solution of system response and extraction of time-frequency characteristics in a unified mathematical framework, and realizes high-precision time-frequency joint characterization by directly solving wavelet coefficients, thereby overcoming inherent defects of an existing two-step method.

The application relates to a precision double-drive motion platform synchronization control method based on a composite adaptive online estimation, and relates to the field of precision motion platform cooperative control.The application solves the problems of poor task tracking performance and low synchronization performance of a double-drive motion platform.In the application, a B-spline wavelet neural network online identification model generates a neural network weight matrix through a specially designed neural network weight composite update model to update the neural network weight matrix, unknown parameters of the system are updated through a constructed system parameter composite update model, a double-drive motion platform is compensated in real time through a constructed expected compensation model, the double-drive motion platform system unmodeled dynamics and external disturbance are compensated through a constructed B-spline wavelet neural network online identification model, and then a robust feedback controller is constructed to perform robust stabilization, so that the task tracking performance and synchronization of the double-drive motion platform are improved.The application is mainly used for synchronously controlling a double-drive gantry motion platform.

The application relates to the field of communication and specifically provides a Fresnel reflection optical fiber diagnosis method and system, which comprises the following steps: collecting a Fresnel reflection signal of a to-be-detected optical fiber to obtain a one-dimensional original time domain signal sequence; adopting a multi-scale decomposition algorithm, taking an asymmetric fractional B-spline wavelet low-pass filter as a convolution kernel to carry out smooth filtering and two-division down-sampling processing on the signal; combining up-sampling and filter difference operation to solve detail components layer by layer until a preset decomposition layer number is reached; calculating a normalized interlayer difference kurtosis to construct a noise suppression factor and weighting denoising of the first scale detail component; up-sampling each scale detail component after denoising to the original signal length, and generating a multi-dimensional feature vector by aggregating components at each time point; calculating the L2 norm square of the time gradient of the feature vector to obtain corresponding fault characteristic values and synthesize a one-dimensional fault feature map; setting a judgment threshold value, positioning the Fresnel reflection position, identifying faults, and realizing optical fiber fault detection and positioning.

A traveling wave ranging method, device and storage medium applicable to a distribution network according to the present invention include first, for the traveling wave of the fault phase current, preprocessing the double-ended current traveling wave through normalization and rough zero-phase band-pass filtering in the characteristic frequency band; using spline wavelet transform to calibrate appropriate modulus maximum points as the preliminary estimation of the wave head starting point; then further estimating the wave head on the double-ended time-domain original traveling wave waveform by using the threshold method, and obtaining the accurate wave head starting point through double-ended amplitude interpolation calibration; finally, calculating the fault point position according to the double-ended traveling wave ranging principle. The present invention preprocesses the fault phase current waveform into a current traveling wave in a rough characteristic frequency band through zero-phase filtering means, eliminates the interference outside the characteristic frequency band, takes the wave head inflection point as the wave head starting point, gradually estimates the inflection point through wavelet modulus maximum and signal amplitude threshold methods, and then obtains a more accurate approximation of the inflection point through double-ended amplitude interpolation, so as to achieve a ranging accuracy beyond the sampling rate limit.

The invention discloses a piecewise B-spline wavelet periodic response calculation method for a collision vibration system, which comprises the following steps: (1) establishing a dynamic equation for wavelet discretization, discretizing a dynamic control equation of a collision-vibration system by using a 4-order B-spline wavelet basis function, and establishing a nonlinear algebraic equation set about a wavelet coefficient; (2) carrying out segmented iterative solution on the time domain, dividing the whole time domain into a plurality of sub-time periods which are connected in sequence, and carrying out iterative solution on the nonlinear algebraic equation set in each sub-time period to obtain a global wavelet coefficient; and (3) establishing periodic response reconstruction and analysis, reconstructing displacement, speed and acceleration response of the system based on the wavelet coefficient, and judging periodic response characteristics through judgment conditions. The invention aims to provide a method for calculating the periodic response of a collision-vibration system directly, accurately and efficiently based on a segmented 4-order B-spline wavelet technology.

The application relates to the technical field of power fault identification, and discloses a traveling wave fault positioning method and system. The method is used for positioning a traveling wave fault by screening two traveling wave collecting devices with opposite traveling wave directions and the closest distance, constructing a cubic B-spline wavelet as a wavelet base, performing wavelet decomposition on the traveling wave signals of the screened traveling wave collecting devices, obtaining the highest frequency harmonic component, simulating the harmonic component, determining the fault section in the direction of the first mutation point of the harmonic spectrum obtained through simulation at scale 1, obtaining the wavelet coefficient modulus maximum point at scale 4 of the harmonic spectrum and the corresponding modulus maximum value, calculating the fault time according to the modulus maximum value and the sampling frequency, and calculating the specific position of the fault point in the fault section by using the fault time, so that the fault positioning accuracy is improved.

The invention discloses an English syllable u feature wavelet coefficient extraction method based on a spline interpolation wavelet neural network, and the method comprises the steps: firstly carrying out the normalization and threshold preprocessing of an audio signal, and effectively removing the interference of environment noise; secondly, constructing a three-layer neural network feedback matrix based on a six-order spline wavelet function, and generating a feedback matrix through transposition operation and inverse matrix calculation of a global matrix psi; then, inverse discrete Fourier transform is utilized to construct a criterion function containing frequency domain errors; and finally, dynamically adjusting the weight of an output layer through iterative training, and terminating training when the modulus value of the criterion function is smaller than a training error iteration ending condition, so as to obtain a wavelet coefficient set representing the characteristics of the longhairy sound u. According to the method, the frequency domain localization characteristic of the six-order spline wavelet is innovatively combined with the adaptive learning of the neural network, the anti-noise performance is improved while the feature extraction precision is ensured, and the problem of individual pronunciation difference is solved.

The present invention discloses a method for extracting characteristic wavelet coefficients of the English long vowel u based on a spline interpolation wavelet neural network. The method first normalizes and thresholds the audio signal to effectively remove environmental noise interference. Secondly, a three-layer neural network feedback matrix based on a sixth-order spline wavelet function is constructed, and the feedback matrix is generated by transposing the global matrix Ψ and calculating the inverse matrix. Then, a criterion function containing frequency domain errors is constructed using an inverse discrete Fourier transform. Finally, the output layer weights are dynamically adjusted through iterative training. When the criterion function modulus is less than the training error iteration end condition, the training is terminated to obtain a set of wavelet coefficients representing the characteristics of the long vowel u. The present invention innovatively combines the frequency domain localization characteristics of the sixth-order spline wavelet with the adaptive learning of the neural network, improving the noise resistance performance while ensuring feature extraction accuracy, and solving the problem of individual pronunciation differences.

The invention discloses a parafoil system trajectory planning method, a parafoil system trajectory planning device and parafoil system trajectory planning equipment based on interval spline wavelets. Establishing a parafoil dynamic model, and constructing an interval spline wavelet basis function; defining a trajectory planning process of the parafoil system as an optimal control problem, namely searching a control variable, a state variable, a fixed initial moment and a free end moment, enabling a performance index to be minimum, and determining a constraint condition; dispersing a time interval into multiple layers of collocation points, expanding a state variable and a control variable on the collocation points, converting a constraint condition into a wavelet coefficient form, and converting an optimal control problem into a nonlinear programming problem; and solving the nonlinear planning problem to obtain a trajectory planning result of the parafoil system. The method is applied to the field of aircraft trajectory optimization, the trajectory planning process of the parafoil system is converted into a nonlinear planning problem from an original optimal control problem, the calculation dimension is remarkably reduced, endpoint constraint can be strictly met, and trajectory mutation can be adaptively captured.

The application discloses a wing parachute system trajectory planning method, device and equipment based on interval spline wavelet, and the method comprises the steps of establishing a wing parachute dynamics model, constructing an interval spline wavelet base function, defining a wing parachute system trajectory planning process as an optimal control problem, that is, finding control variables and state variables, a fixed initial time and a free end time, minimizing a performance index, and determining constraint conditions, discretizing a time interval into multiple layers of collocation points, expanding state variables and control variables on the collocation points, and converting the constraint conditions into wavelet coefficient form, converting the optimal control problem into a nonlinear programming problem, and solving the nonlinear programming problem to obtain a wing parachute system trajectory planning result. The application is applied to the field of aircraft trajectory optimization, converts the wing parachute system trajectory planning process from an original optimal control problem into a nonlinear programming problem, significantly reduces the calculation dimension, and can strictly meet the end point constraint and adaptively capture trajectory mutation.

The invention discloses an industrial image denoising method and system based on cardinal number type polishing spline wavelets, and relates to the technical field of image processing. The method comprises the steps that a cubic cardinal number type polishing spline function serves as a scaling function, a cardinal number type polishing spline wavelet function with an explicit analytical expression is constructed, a dual-scale equation is established, and coefficients are derived. And carrying out frequency domain processing on the coefficient, and obtaining a reconstructed filter impulse response coefficient according to a complete reconstruction condition, namely, a dual wavelet dual-scale coefficient. A target industrial image is used as initial data, layer wavelet decomposition and nonlinear adaptive threshold processing are carried out through a reconstruction filter and a Mallat dual-channel filter bank to obtain approximation and detail information, then the image is reconstructed through Mallat inverse transformation, and denoising and detail protection are achieved.

The invention relates to a seismic data frequency band expanding method, device and equipment and a medium, and belongs to the field of seismic exploration data processing.The seismic data frequency band expanding method comprises the steps that a pseudo reflection coefficient sequence is obtained according to an extracted work area logging curve; setting an expanded frequency band according to the frequency band of the seismic data in the work area, generating a Ricker wavelet consistent with the main frequency of the seismic data, constructing a broadband B-spline wavelet based on the expanded frequency band, and respectively performing convolution processing on the broadband B-spline wavelet and the Ricker wavelet with the pseudo reflection coefficient sequence to obtain a narrow frequency band and broadband seismic data; the constructed DAU-Net model is trained based on the narrow-band and wide-band seismic data, the to-be-predicted narrow-band seismic data is predicted based on the completely trained DAU-Net model, the predicted wide-band seismic data is obtained, and the resolution of the seismic data is improved.

The application provides an ultrasonic guided wave dispersion curve calculation method, and belongs to the technical field of ultrasonic measurement. With the increase of the thickness of a to-be-measured plate structure and the increase of the complexity of the structure, if a traditional finite element analysis method is used when a finite element model of the to-be-measured plate structure is constructed, a high-order polynomial interpolation function needs to be used, and a large number of units need to be divided, so that the number of finite element grids increases, and the calculation efficiency is reduced. In the application, the shape function of an interval B-spline small element is used as an interpolation function for solving, the calculation accuracy can be ensured, a large number of units do not need to be divided, the number of finite element grids is reduced, and the calculation efficiency can be improved.