15 results about "Harmonic model" patented technology

The invention relates to the field of voice signal processing and voice recognition, and discloses a voice recognition enhancement method and system based on harmonic model fundamental frequency optimization and RNN noise suppression, and the method comprises the steps: collecting a voice signal in a noise environment in real time, carrying out the framing and windowing of the voice signal, and generating multi-dimensional time-frequency data; estimating the fundamental frequency of each frame of voice through a cepstrum analysis method, and screening effective fundamental frequency frames according to a confidence coefficient threshold to form a fundamental frequency characteristic matrix; dynamically adjusting the noise power spectrum of the Wiener filter under the drive of the fundamental frequency characteristic matrix, and carrying out dislocation fusion on the filtering output and the original spectrum to form an enhanced spectrum first draft; inputting the enhanced spectrum first draft into a recurrent neural network in a framing manner, predicting the gain of each frequency band, calculating an inhibition factor, and generating a multi-frame continuous enhanced spectrum sequence; multiple frames of continuous enhanced spectrum sequences are synthesized into voice signals through inverse short-time Fourier transform, an end-to-end enhanced recognition process is formed, and the method has the advantage of improving accuracy.

The invention discloses a dual three-phase permanent magnet synchronous motor harmonic suppression method based on virtual back electromotive force identification, and the method comprises the following steps: S1, building a driving system model of a DTP-PMSM; s2, constructing a harmonic model of the DTP-PMSM, analytically decomposing the nonlinear characteristic and the non-sinusoidal counter electromotive force of the inverter into dq and dqz subspaces, introducing the concept of virtual harmonic counter electromotive force, and unifying the nonlinearity of the inverter, the space harmonic counter electromotive force and cross coupling terms related to harmonic current into a single expression form; and S3, developing an identification principle based on current mapping, including amplitude and phase estimation, gain design and delay compensation, so as to estimate the amplitude and phase deviation of the virtual harmonic back electromotive force on line to realize harmonic suppression and avoid a complex algorithm and a large amount of parameter adjustment. According to the method, the operation effect is good in a wide rotating speed range, and meanwhile complex algorithms and a large amount of parameter adjustment are avoided.

The application discloses a kind of human activity influence assessment methods of forestry ecological diversity, comprising: the historical remote sensing image sequence of target area is collected, the reflectivity of pixel is fitted as continuous harmonic model;Harmonic model is used to calculate the reflectivity of pixel fitting, and the mutation pixel is screened out, and then the mutation point that human activity produces disturbance to target area is identified;The normalized disturbance index of pixel is calculated, and the habitat suitability index of pixel is obtained;The habitat suitability index of pixel is calculated, and the suitable habitat pixel is screened out, and the maximum activity radius and ecological area of organism in suitable habitat patch are calculated;Ecological diversity influence coefficient is calculated, and the influence situation of human activity on the ecological diversity of target area is evaluated.The application uses long time sequence remote sensing to quantize disturbance and recovery track, can identify short-term interference and long-term recovery process, realize the time sequence correlation evaluation of " change process-ecological response ".It provides data support for forestry sustainable management and ecological protection.

The invention discloses a method for evaluating the influence of human activities on the ecological diversity of forestry, and the method comprises the steps: collecting a historical remote sensing image sequence of a target region, and fitting the reflectivity of pixels into a continuous harmonic model; calculating the reflectivity of pixel fitting by using a harmonic model, screening out abrupt change pixels, and further identifying abrupt change points where human activities disturb the target area; calculating a normalized disturbance index of the pixel to obtain a habitat suitability index of the pixel; calculating habitat suitability indexes of the pixels, screening suitable habitat pixels, and calculating the maximum activity radius and ecological area of organisms in suitable habitat plaques; and calculating an ecological diversity influence coefficient, and evaluating the ecological diversity influence condition of the human activities on the target area. According to the method, disturbance and recovery tracks are quantified by using long-time sequence remote sensing depth, short-term interference and long-term recovery processes can be identified, and'change process-ecological response 'time sequence correlation evaluation is realized. And data support is provided for sustainable management and ecological protection of forestry.

The invention belongs to the technical field of permanent magnet synchronous motors, and discloses a resonance-interaction cascade expansion state observer, device and method, and the method comprises the following steps: converting a three-phase stator current into a d-axis current and a q-axis current under a d-q synchronous rotating coordinate system according to a current harmonic model of a permanent magnet synchronous motor; d-axis current and q-axis current are calculated, d-axis voltage and q-axis voltage are calculated, the d-axis current, the q-axis current, the d-axis voltage and the q-axis voltage are injected into the resonance-interaction cascade expansion state observer, and an estimated value and a compensation voltage value of input current are obtained; and injecting the generated compensation voltage value into a vector control current inner ring of the permanent magnet synchronous motor, and adding the compensation voltage value with the d-axis voltage and the q-axis voltage. According to the method, the dynamic performance and the steady-state performance of the system in a small time scale can be improved, the accuracy of the generated compensation voltage can be ensured, the influence of the performance defect of the observer on the current harmonic suppression effect is reduced, and the error of current harmonic tracking is reduced on the premise of ensuring the rapidity.

The invention discloses an inductance harmonic measurement and analysis method, which is based on an alternating current static measurement method and comprises the following steps of: 1, establishing an inductance harmonic model: respectively constructing a self-inductance model of a stator winding, an inter-phase mutual inductance model and a self-inductance and mutual inductance matrix model of a three-phase winding; 2, an alternating current static measurement circuit is adopted, alternating current with a fixed frequency is introduced into two-phase windings of the motor, a motor rotor is kept static at different space angle positions, and voltage and current parameters between the two phases are measured; step 3, based on a measurement result, calculating to obtain a comprehensive inductance parameter which is LAA-MAB + LBB-MAB and changes along with the rotor position angle theta; and 4, extracting second-order and fourth-order harmonic amplitudes of the inductor to obtain the harmonic content of the inductor of the motor. According to the method, the second-order and fourth-order harmonic amplitudes of the winding inductance of the permanent magnet synchronous motor can be accurately extracted, so that the harmonic content of the inductance of the motor body related to second-order and fourth-order noise is effectively evaluated, and accurate inductance harmonic data is provided for noise optimization of an EPS system.

This invention belongs to the field of harmonic analysis technology and provides a method and system for harmonic modeling of server clusters based on operating condition clustering. It acquires multi-dimensional operating condition parameters of a single server, preprocesses the acquired data, matches the preprocessed data with a preset equivalent operating condition class of server harmonic characteristics, calls the corresponding dedicated harmonic model, and superimposes them to obtain the harmonic model of the server cluster. If the operating condition parameters do not fall within the parameter range of any preset equivalent operating condition class, it is considered a newly added equivalent operating condition class, and the corresponding dedicated harmonic model is fitted to the dedicated harmonic model library. This invention achieves adaptive calculation of the server cluster harmonic model, reduces the computational complexity of the model, and improves the calculation speed and modeling accuracy.

The application discloses a polar motion prediction method considering period time-varying characteristics, belongs to the technical field of space geodetic measurement, and is used for polar motion prediction and comprises the following steps: preparing a data set, constructing a polar motion complex time sequence, and determining optimal period parameters by using a differential evolution algorithm adaptive optimization; a complex domain harmonic model is constructed to calculate polar motion prediction values, and the fitting prediction values are extrapolated; an autoregressive model is constructed to calculate residual sequence prediction values; and the fitting prediction values and the residual sequence prediction values are added to obtain final polar motion prediction results. By introducing a differential evolution algorithm global optimization algorithm to adaptively determine time-varying period parameters in the polar motion sequence, more accurate fitting and prediction of key elements such as period, amplitude and phase change of Chandler wobble and annual term in the polar motion signal are realized, a more stable residual sequence is provided for the autoregressive model, and the accuracy and stability of polar motion prediction, especially medium and long term span prediction, are significantly improved as a whole.

The invention relates to an M3C double-fundamental-frequency coupling characterization method, device, equipment and medium, and the method comprises the steps: building a basic dynamic equation of bridge arm electrical parameters based on an M3C average value model; based on the basic dynamic equation, performing frequency domain decomposition and matrix representation on the electrical parameters under power frequency and low frequency conditions to generate a two-dimensional frequency domain matrix; performing linear equivalent modeling on the frequency domain operation relation of the two-dimensional frequency domain matrix to obtain a structured matrix; dimensionality reduction processing is carried out on the structured matrix, and steady-state frequency representation of the bridge arm electrical parameters is obtained; and based on the steady-state frequency representation, deducing to obtain a steady-state frequency domain harmonic model of the bridge arm loop. The method has the effect of improving the accuracy of analyzing the steady-state frequency characteristics of the electrical parameters of the bridge arm by the M3C.

The application relates to a DC power distribution network harmonic modeling method based on a substitution theorem, and comprises the following steps: classifying each key device in a DC power distribution network according to the function of electric energy transformation; processing the input end and the output end of each type of device; writing the state space average equation of each device; obtaining the exponential Fourier coefficients of each variable in the state space average equation and bringing the exponential Fourier coefficients into the state space equation to obtain the harmonic state space model of each type of device, and then converting the frequency domain expression of each variable into a time domain expression through a Fourier series expansion formula; and building a harmonic model of the DC power distribution network according to the substitution theorem. Compared with the prior art, the application adopts a harmonic modeling method to perform harmonic analysis on each variable in the DC power distribution network system, and solves the problem that the harmonic state space modeling method is not suitable for large and complex systems.

This invention relates to the field of eddy current position sensor testing technology, and particularly to a calibration and compensation testing method for an eddy current position sensor test bench. The method comprises: S1, acquiring and preprocessing the output signal of the eddy current sensor; S2, performing calibration and compensation processing on the sine and cosine voltage signals to be compensated, obtaining calibrated compensated sine and cosine voltage signals; the sine and cosine voltage signal compensation processing includes at least one of the following: offset compensation and amplitude correction; S3, calculating and determining the angular position information of the eddy current position sensor; and S4, performing harmonic analysis on the signal using Fourier transform to obtain higher-order harmonic models under four conditions: initial position of the rotor relative to the stator, axial offset, radial offset, and tilt angle change. This invention significantly improves the accuracy of test results when testing eddy current sensor products by using offset compensation of the sine and cosine analog voltage signals, amplitude correction of the sine and cosine analog voltage signals, and rapid positioning through harmonic analysis.

The invention relates to the technical field of battery safety and health management, and discloses a battery cell waistcoat stress distribution real-time monitoring method, which comprises the following steps of: firstly, establishing a stress frequency temperature model and a state harmonic model through offline calibration; during on-line monitoring, the system generates and picks up a magnetic-acoustic coupling response signal on the waistcoat through the excitation-pickup array. The method comprises the following steps of: extracting fundamental resonant frequency and harmonic feature vectors by performing fast Fourier transform on a signal; according to the invention, the fundamental resonant frequency is creatively combined with temperature input to accurately quantify the stress, so that self-compensation of temperature influence is realized; meanwhile, the stress type and the early-stage micro-damage state are cooperatively interpreted by using fingerprint characteristics of harmonic feature vectors. According to the invention, two-dimensional and full-field stress and structure health state integrated evaluation can be carried out on the surface of the battery cell, monitoring information is comprehensive, the temperature interference resistance is high, the system can be easily integrated in a sealed battery pack, and the accuracy and practicability of battery state monitoring are obviously improved.

The invention discloses an SRM harmonic closed-loop torque ripple suppression method based on current square. The method comprises the following steps: (1) constructing an electromagnetic torque expression containing current square, and solving a current square harmonic model with optimal torque ripple; (2) obtaining a current square model with an optimal current square direct current bias value and an optimal torque ripple; (3) generating a fundamental wave amplitude reference value of the current square model with the optimal torque ripple, and obtaining a current square excitation model in an actual injection motor and an actual current square model of an output motor; (4) in order to realize closed-loop suppression of the torque ripple, the auxiliary channel executes a correction process; and (5) compensating an instantaneous torque peak appearing in a specific electrical angle range, completing harmonic closed-loop torque ripple suppression, and realizing an optimal torque ripple scheme. According to the invention, a double-layer compensation architecture based on current square harmonic injection and torque real-time feedback is constructed, so that the systematic suppression of the torque ripple of the switched reluctance motor is realized.

The application belongs to the technical field of power system power quality analysis, and provides a harmonic modeling method for large-scale charging and discharging stations, including: collecting measured three-phase voltage signals and three-phase current signals in the historical operation of the large station, performing Fourier transform on the three-phase voltage signals and three-phase current signals according to the Nuttall window function, extracting voltage phasors and current phasors corresponding to each harmonic, then based on the voltage phasors and current phasors corresponding to each harmonic, constructing a harmonic coupling matrix model, and using n groups of measured harmonic voltage and harmonic current data, using a complex domain partial least squares method to solve the parameters of the harmonic coupling matrix model, finally introducing voltage similarity as a model updating criterion to dynamically update the harmonic coupling matrix model, and establishing a dynamic harmonic model suitable for different operating states. The application can significantly improve the accuracy and working condition adaptability of the harmonic modeling of the large-scale charging and discharging station by constructing the harmonic coupling matrix and dynamically updating.

The invention discloses an urban vegetation change detection method and system based on improved CCDC-SMA, and belongs to the technical field of remote sensing monitoring and image processing. The method comprises the following steps: firstly, constructing a universal end member spectrum library suitable for different cities, and extracting green vegetation abundance and other characteristics from a Landsat time sequence image by using spectrum hybrid analysis; secondly, proposing an improved harmonic model, enabling the model to describe the non-stationary trend of vegetation growth by increasing an interannual change coefficient item, and carrying out fitting by adopting a Levenberg-Marquardt algorithm; and finally, carrying out continuous change detection and interruption judgment on the multi-feature time sequence based on the model. According to the method, the problems of high false drop rate, insensitivity to mixed pixel change and poor regional universality caused by mismatching of model hypothesis and vegetation growth characteristics in a traditional method are effectively solved, and the precision, robustness and generalizability of dynamic monitoring of urban vegetation are remarkably improved; and an efficient and reliable technical means is provided for urban ecological research and management.