24 results about "Discrete time domain" patented technology

A method for extracting a wear particle feature signal based on segmentation entropy is provided, including obtaining a raw signal to be processed by performing real-time data acquisition using a lubricating oil wear particle monitoring system; obtaining a preprocessed signal by performing low-pass filtering and harmonic interference suppression on the raw signal to be processed; dividing the preprocessed signal into a plurality of time domain sequence segments with a sliding window; calculating segmentation entropy corresponding to each time domain sequence segment, normalizing a segmentation entropy set to obtain normalized segmentation entropy; obtaining an adaptive threshold through curve fitting based on empirical cumulative distribution of normalized segmentation entropy, obtaining a plurality of non-zero discrete time domain signal segments by segmenting the preprocessed signal by the adaptive threshold; and obtaining final extraction results of the wear particle feature signal by excluding residual noise interference through target signal feature recognition indices.

The invention discloses a harmonic and inter-harmonic parameter detection method and device based on a self-multiplication convolution window algorithm, and belongs to the field of signal detection, and the method comprises the steps: obtaining a discrete time domain signal, and carrying out the windowing and mapping of the time domain signal based on the self-multiplication convolution window algorithm, and obtaining a frequency domain signal; calling a quantum particle swarm algorithm to estimate the frequency domain signal to obtain an estimation parameter matched with a preset frequency spectrum; and performing nonlinear error compensation on the estimation parameter by using a preset space-time attention residual network to obtain harmonic and inter-harmonic parameters. According to the method, signal leakage can be suppressed by windowing the signal, the energy of the main lobe of the frequency spectrum is more concentrated, the frequency domain signal is estimated by using the quantum particle swarm algorithm, the evaluated frequency spectrum meeting the actual demand can be quickly screened, and finally, the frequency spectrum is compensated, so that the error can be further reduced, and the detection precision can be further improved.

The invention discloses a power distribution network multi-type flexible resource low-carbon scheduling method based on carbon emission flow, and relates to the technical field of power system low-carbon scheduling, and the method comprises the steps: constructing a scheduling time period set of a discrete time domain, and building an equivalent lossless network model; power flow calculation is carried out, and a node-branch carbon flow mapping relation is established; according to the carbon emission intensity of the unit, the carbon flow rate and node carbon emission flow of each branch are calculated; performing differential approximate calculation on the node injection power to obtain a carbon marginal coefficient of each node; generating a time-varying carbon price signal of each node in combination with an external carbon price reference; constructing a weighted combination objective function based on the node time-varying carbon price signal; and solving a weighted combination objective function and constraint conditions by adopting a distributed multi-agent collaborative optimization strategy. According to the invention, collaborative scheduling of multiple types of flexible resources under a low-carbon target is realized, and the carbon emission reduction effect is improved.

The application relates to the field of circuit state space equation solving technology in the real-time simulation field, and discloses a state space equation discretization method for capacitor and inductor element characteristics, which comprises the following steps: A) establishing a state space differential equation of a circuit; B) establishing a characteristic equation of a capacitor and an inductor element, determining a numerical integration method used by each capacitor and inductor element in the circuit, and obtaining a discrete time domain characteristic equation by using the numerical integration method; C) combining the discrete time domain characteristic equation of step B) and the state space differential equation of step A) to obtain a state space discrete equation of the circuit; and D) cyclic simulation. The state space equation discretization method for capacitor and inductor element characteristics improves the speed and precision of real-time simulation of a circuit system by independently discretizing the characteristic equations of each capacitor and inductor element and optimizing the discretization process of the state space equation.

The invention provides a wind turbine generator rotating shaft fault monitoring method and system based on pulse amplitude modulation. The method comprises the steps that pulse amplitude modulation signals of a rotating shaft are collected through a pulse amplitude modulation measuring device installed on a target shaft section of the rotating shaft of a measured wind turbine generator; performing amplitude demodulation on the pulse amplitude modulation signal to obtain an eccentric compound vibration component of the rotating shaft; carrying out discretization processing to obtain a composite vibration component sequence of a discrete time domain, then carrying out Fourier transform on the sequence of the discrete time domain to obtain phase differences, and extracting vibration amplitudes and amplitude characteristic parameters of each vibration component under different frequencies; and monitoring a misalignment abnormal state of the rotating shaft according to the vibration amplitudes, the amplitude characteristic parameters and the phase differences of the vibration components under different frequencies. According to the technical scheme, signals are collected through the pulse amplitude modulation measuring device, and high-precision monitoring and accurate fault type identification of the misalignment of the rotating shaft of the wind turbine generator are realized in combination with amplitude demodulation and frequency domain analysis.

The invention discloses an unmanned aerial vehicle anti-interference inhabitation trajectory planning method and system, a medium, equipment and a product in the technical field of unmanned aerial vehicle inspection. The method comprises the steps of performing real-time positioning on an unmanned aerial vehicle through a sensor loaded on the unmanned aerial vehicle and an environmental map constructed by SLAM, and generating an unmanned aerial vehicle reference path by using a mixed A * optimization algorithm based on node expansion; according to the obtained environmental influence data, performing environmental influence prediction by using the trained LSTM model to obtain an environmental influence prediction sequence; and according to the current position of the unmanned aerial vehicle, the current speed of the unmanned aerial vehicle, the environmental influence prediction sequence and the reference path of the unmanned aerial vehicle, constructing a discrete time domain flight state equation, and generating a flight path of the unmanned aerial vehicle based on an improved model prediction control framework MPC. The method is high in real-time performance, high in anti-interference capability and stable in tracking precision, and ensures that the unmanned aerial vehicle completes a precise, safe and efficient inspection task in an environment influenced by the environment.

The application discloses a disturbance-resistant multi-agent discrete-continuous hybrid specified-time state estimation method, and belongs to the field of distributed state estimation of multi-agent systems, and comprises the following steps: S1, considering the state dynamics of the multi-agent system and the influence of external disturbance, a dynamic equation of the multi-agent system is constructed; S2, based on the dynamic equation of the multi-agent system, an augmented state estimation error equation and an extended state observer of the multi-agent system are constructed; S3, an estimation error dynamic equation in a discrete time domain is constructed, and the convergence of the augmented state estimation error is analyzed; S4, a discrete sampling interval is designed, so that the augmented state estimation error converges to zero within a specified time. The above-mentioned disturbance-resistant multi-agent discrete-continuous hybrid specified-time state estimation method can effectively cope with external disturbance, fuse the advantages of discrete and continuous time, be faster, more accurate and robust, and ensure that the state estimation of the multi-agent system is efficient and reliable.

The invention discloses a two-dimensional wave field reconstruction method, device and terminal based on spatial sparse sampling, and the method comprises the steps: obtaining an original two-dimensional time domain signal corresponding to an original signal, carrying out the compression sampling of the original two-dimensional time domain signal, and determining a two-dimensional discrete time domain signal; fourier transform is carried out on the two-dimensional discrete time domain signal, and a two-dimensional discrete frequency domain signal is determined; solving a two-dimensional wave number signal according to the two-dimensional discrete frequency domain signal based on a compressed sensing theory; and performing inverse Fourier transform on the two-dimensional wave number signal, determining a reconstructed two-dimensional time domain signal, and determining a reconstructed signal corresponding to the original signal according to the reconstructed two-dimensional time domain signal. According to the invention, the two-dimensional wave number signal is reconstructed according to the two-dimensional discrete frequency domain signal obtained by sampling through compressed sensing, and the reconstructed signal corresponding to the original signal is obtained according to the two-dimensional wave number signal, so that the problem that the two-dimensional wave field data is sampled by adopting Nyquist in the prior art can be effectively solved; the data redundancy is high; and the transmission pressure is large.

The invention belongs to the technical field of fuel cells, and discloses a direct identification method for equivalent circuit model parameters of a hydrogen fuel cell. The method comprises the following steps: firstly, establishing an R-(RC)-(RC)-(RC) equivalent circuit model and a frequency domain transfer function of the R-(RC)-(RC) equivalent circuit model according to response characteristics of an internal electrochemical reaction of a fuel cell in different frequency bands of an impedance spectrum; secondly, the continuous transfer function is converted into an input and output equation of a discrete time domain through variable substitution and bilinear transformation, and an identifiable mathematical model of the parameters to be identified is formed; then, a recursive least square method containing a forgetting factor is adopted, and the coefficient of the mathematical model is identified online in real time; and finally, reversely resolving all impedance parameters of the equivalent circuit based on an identification result, and drawing an electrochemical impedance spectrum curve according to the impedance parameters. According to the invention, the online rapid identification of the impedance parameter can be realized only by using the output voltage and current data during the normal operation of the fuel cell without injecting any external excitation signal.

The application belongs to the technical field of marine monitoring, and discloses a wave spectrum analysis method and system based on a laser radar.The method comprises the following steps: obtaining a plurality of concentric circles in the obtained wave field point cloud data; matching the discrete time domain signals of the wave height corresponding to the concentric circles and the derivative of the wave height with respect to time, and calculating the discrete values of the amplitude of the wave spectrum with respect to frequency; calculating unknown parameters in a directional spread function; and multiplying the discrete values of the amplitude of the wave spectrum with respect to frequency and the spread function to obtain the discrete values of the directional spectrum in frequency and direction, i.e., realizing the analysis of the wave spectrum. Through the application, the problem of realizing the analysis of the wave field spectrum and the directional spectrum by using point cloud data in the analysis of the wave field is solved.

This invention provides a method and apparatus for extracting the time-frequency characteristics of combined impact and corrugation defects in railway tracks. The method includes: determining a window length limit based on the discrete-time domain signal; using a third-order B-spline function as the window function for the Short-Time Fourier Transform (STFT) based on the discrete-time domain signal to determine the initial STFT time-frequency diagram and the initial Rayleigh entropy; utilizing the recursive property of the third-order B-spline function as the window function to determine the STFT result sequence and the Rayleigh entropy sequence of equal-length window sequences; determining the time-frequency transformation result and the optimal Rayleigh entropy based on the window length limit, the initial STFT time-frequency diagram, the initial Rayleigh entropy, the STFT result sequence, and the Rayleigh entropy sequence; and determining the time-frequency characteristics of the impact signal and the corrugation signal based on the time-frequency transformation result and the optimal Rayleigh entropy. This invention can simultaneously, quickly, and effectively extract the time-frequency characteristics of the impact component and the corrugation component in railway track defects and express them on a time-frequency diagram.

The invention discloses a frequency correction algorithm for a non-stationary signal, which is characterized in that a signal chain is specially designed, an original target non-stationary signal is divided into two paths after passing through a signal conditioning circuit, one path of signal x1 (t) is directly input to an analog-to-digital converter, and a discrete time domain signal x (n) is obtained after sampling by the analog-to-digital converter; the other path of signal passes through a waveform shaping circuit, a non-stationary signal is converted into a unipolar square wave digital signal x2 (t), the signal enters a digital processor with pulse capture and timer technical functions as a digital signal, and the digital processor can obtain a frequency value fc of the signal x2 (t) after passing through the waveform shaping circuit by adopting an equal-precision frequency measurement method; fc is defined as coarse frequency. Under the condition that all original time domain information of the signal is reserved, the judgment coefficient gamma is calculated by dividing frequency spectrum and power spectrum intervals, and the corresponding frequency correction formula is selected according to the value range of the judgment coefficient gamma, so that the accurate frequency correction of the non-stationary signal is realized, and the data measurement accuracy is improved.

The invention discloses a methanol reforming fuel cell modeling and parameter identification method and application, and the method comprises the following steps: using combustion chamber temperature, reforming chamber inlet temperature and outlet temperature as state variables, defining a state vector, using combustion chamber methanol or tail gas feed, air feed and reforming chamber methanol feed as input, defining an input vector, and using combustion chamber methanol or tail gas feed, air feed and reforming chamber methanol feed as state variables; establishing a discrete time domain state space model; s2, disassembling the discrete time domain state space model into a scalar equation; s3, collecting experimental data, wherein the experimental data comprises any one or more of combustion chamber temperature, reforming chamber inlet and outlet temperature, combustion chamber methanol or tail gas feeding, air feeding and reforming chamber methanol feeding; and S4, constructing an error objective function and performing parameter identification by adopting a particle swarm optimization algorithm to obtain a model for simulation and control. According to the method, the dynamic process of preheating and power generation stages can be effectively reflected, and support is provided for system simulation, control and operation optimization.

The present application relates to a kind of CZT frequency estimation methods, comprising the following steps: S1: the signal to be estimated is sampled, and the maximum spectral line value of the FFT spectrum function is extracted from the frequency index of the FFT spectrum function obtained by the N-point fast Fourier transform of the discrete time domain signal after sampling;S2: the frequency interval of the CZT transform is determined according to the value of the frequency index, and the maximum spectral line value of the CZT spectrum function is extracted from the CZT spectrum function obtained by the discrete time domain signal and the left and right two spectral line values of the CZT spectrum function;S3: the relationship parameter between the maximum spectral line value and the left and right two spectral line values is calculated;S4: error is calculated from the relationship parameter;S5: the estimated frequency of the signal to be estimated is calculated according to the relationship parameter and error.

The embodiment of the application discloses a gain self-adjusting discrete current regulation method of a permanent magnet synchronous motor, relates to the technical field of motor control, and can reduce the calculation amount of high-performance vector control of the permanent magnet synchronous motor while guaranteeing robustness. In the application, a discrete time domain permanent magnet synchronous motor complex vector mathematical model is established, a complex vector current regulator is designed through zero-pole configuration and internal model principle, and a multi-gain parameter online identification and self-adjusting method is provided. The current control method can realize high-performance vector control of the permanent magnet synchronous motor, and has the advantages of small calculation amount, strong robustness and the like.

The application discloses a kind of underwater rotating machinery multi-component vibration signal decoupling methods based on order analysis.Method includes: first, the discrete time domain vibration signal of underwater rotating machinery is obtained by superimposing multiple harmonic components;Then the discrete time domain vibration signal is transformed into angular domain signal, performs discrete Fourier transform, and extracts the amplitude spectrum of each order component;On this basis, the order amplitude spectrum is identified by using multi-peak detection algorithm, and the main order component order set is screened out;Finally, the time domain waveform corresponding to the main order component is extracted by order decoupling method.The application can effectively decouple the multi-component vibration signal in underwater rotating machinery, and provide quantitative basis for locating excitation source, analyzing excitation source characteristics or fault diagnosis.

The present application relates to the technical field of electromagnetic scattering, and particularly relates to a method and device for calculating frequency domain response of electromagnetic field, equipment and storage medium; a time domain basic system equation is recursively transformed according to a discrete time domain set and a backward Euler method to obtain a time domain transformation equation and an algebraic matrix equation; the algebraic matrix equation is back-substituted and solved according to a time domain stepping method and the time domain transformation equation; a time domain finite element solution is calculated based on a time domain finite element method to obtain a time domain base solution; the time domain base solution is calculated according to a preset linear superposition principle to obtain a frequency domain response; a continuous problem is discretized by the backward Euler method, and a fast back-substitution solution is obtained after one factor decomposition to reduce redundant calculation; the time domain base solution is phase-weighted and synthesized based on the linear superposition principle to quickly obtain an arbitrary frequency domain response, avoid repeated calculation for each frequency, improve efficiency, be suitable for wideband high-precision electromagnetic field analysis, and have significant application value.

The application belongs to the technical field of fuel cells, and discloses a hydrogen fuel cell equivalent circuit model parameter direct identification method. First, according to the response characteristics of the internal electrochemical reaction of the fuel cell in different frequency bands of the impedance spectrum, an R-(RC)-(RC)-(RC) equivalent circuit model and its frequency domain transfer function are established. Second, the continuous transfer function is converted into an input-output equation in the discrete time domain through variable substitution and bilinear transformation, forming an identifiable mathematical model of the to-be-identified parameters. Then, the recursive least squares method with a forgetting factor is used to identify the coefficients of the mathematical model in real time. Finally, all impedance parameters of the equivalent circuit are solved reversely based on the identification result, and an electrochemical impedance spectrum curve is drawn accordingly. The application only needs to use the output voltage and current data of the fuel cell during normal operation, without injecting any external excitation signal, so that the online rapid identification of the impedance parameters can be realized.

The invention discloses a radar ranging method based on frequency domain phase correction, which comprises the following steps: synchronously sampling a transmitted wave signal and a reflected wave signal to respectively obtain discretized time domain signals xt (n) and xr (n), windowing to obtain time domain signal sequences yt (n) and yr (n), and respectively carrying out FFT (Fast Fourier Transform) operation to obtain time domain signal sequences yt (n) and yr (n); a high-precision synchronous analog-to-digital converter is adopted to sample the transmitted wave signal and the reflected wave signal after frequency reduction at the same time to obtain an original time domain discrete signal, FFT is executed after windowing to obtain discrete spectrum data of the signal, and a correction coefficient is obtained through a special phase correction algorithm for calculation; after the phases of the transmitted wave and the reflected wave are corrected, a high-precision transmitted wave phase and a high-precision reflected wave phase are obtained respectively, a high-precision distance value is obtained through the relation between the phase difference and the distance, and high-precision radar ranging is achieved.

The application discloses an impedance automatic modeling method for a frequency-division offshore wind power system, which comprises the following steps: firstly, constructing a mathematical model of an element and linearizing the mathematical model to obtain a continuous time domain small signal model of the element, and discretizing the continuous time domain small signal model through trapezoidal integration to obtain a discrete time domain small signal model of the element; then, based on a correlation matrix and node analysis, converting the discrete time domain model at the element level to a system level model; finally, through z transformation and bilinear transformation, converting the discrete time domain model at the system level to a continuous frequency domain model at the system level, and realizing the above process through codes in a computer to automatically obtain the impedance of the system. The application replaces traditional manual symbolic derivation with numerical calculation, significantly improves the modeling efficiency, has good flexibility and expansibility, can be suitable for complex systems and new topological structures, provides an efficient stability analysis tool for the design and optimization of offshore wind farms and grid-connected systems, and can be extended to other renewable energy grid-connected systems containing multiple power electronic converters.

The invention provides a discrete time domain modal analysis method suitable for an alternating-current and direct-current hybrid system containing multi-port direct current and a related device, which are used for evaluating small disturbance stability and oscillation propagation characteristics of the system. The method comprises the following steps: firstly, constructing a whole-network discrete state matrix, and calculating a characteristic mode to judge a stability and instability mode serial number; determining a main influence area of oscillation through a node voltage observability matrix; and finally, determining an oscillation propagation path in the region by using the branch current observability matrix. According to the method, the limitation that a traditional method is only suitable for a two-port direct current system is solved, the method is expanded to a multi-port direct current scene, and support is provided for oscillation positioning, traceability and stability control strategy formulation of a complex system.

The invention relates to an FI-DAC phase estimation method, in particular to an FI-DAC phase estimation method based on a time domain adaptive phase offset iterative correction algorithm. The invention aims to solve the problem that the existing time domain least square method is difficult to give consideration to both quick response and fine-grained fine tuning in a broadband (10MHz-3GHz) environment due to fixed step length or slow local minimum convergence. According to the method, on the basis of discrete time domain samples of an input signal and an output signal, accurate estimation and correction of phase deviation are completed through seven core steps. The whole process is theoretically equivalent to executing least square fitting on a multi-frequency sine base, and fast and stable convergence is realized by combining a gradient descent strategy of dynamic step size attenuation and momentum acceleration. The invention belongs to the technical field of FI-DAC system phase estimation.

The invention discloses an implicit calculation method for a stress relaxation viscoplastic model of a prestressed steel beam, and relates to the technical field of prestressed concrete structures in the building industry, a rate-type constitutive equation representing stress relaxation is derived based on a fib-2010 stress relaxation model, and a time-step iterative equation is constructed by adopting an implicit Euler format discrete time domain; by defining an intermediate variable and constructing and solving an algebraic equation, calculation of stress increment and updating of a stress state are realized. According to the method, the stress relaxation process of the prestressed steel beam under different time steps is accurately simulated, the coupling relation between concrete creep and prestressed tendon stress relaxation is considered, and the calculation precision is remarkably improved. Meanwhile, the method is suitable for unbonded and bonded prestressed structures, the elastic modulus can be dynamically adjusted according to the stress state, and the applicability of the model is enhanced. In addition, an algebraic equation is solved through implicit Euler format discrete time and a numerical iteration method, and the calculation efficiency is improved.

The application discloses a kind of distribution dynamic load identification method and system based on time variable separation.The method divides distribution load into distribution load function that can be directly separated space-time variable and distribution load function of general form, based on orthogonal polynomial fitting one-dimensional, two-dimensional function theory, respectively in two cases, time domain load is converted into frequency domain load, using Chebyshev orthogonal polynomial is completed in frequency domain to orthogonal polynomial coefficient identification, combined with time domain-frequency domain Fourier transform theory and least square method further completes the distribution time domain dynamic load identification of continuous beam.The application does not need to use a large number of discrete time domain data for modeling, and can directly and clearly represent the identified distribution load;Since only column vector matrix needs to be identified, the identification efficiency is improved based on a large number of reduction of identification calculation data, while the identification accuracy is also guaranteed.