55 results about "Prony method" patented technology

The invention discloses an electric system low frequency oscillation mode identification method based on correlation functions. The method includes the following steps that firstly, a section of an active power signal of a circuit having high observability for a low frequency oscillation mode under the circumstance that no large disturbance exists in an electric system is read and serves as a signal to be analyzed, and a sampling time interval Ts is determined; secondly, the read active power signal is preprocessed to obtain a corresponding power fluctuation signal; thirdly, a self-correlation function of the power fluctuation signal is solved, and a system free oscillation signal is obtained; fourthly, based on an extended Prony method, mode identification is carried out on the free oscillation signal to obtain a low frequency oscillation mode frequency and a damping ratio. The electric system low frequency oscillation mode identification method has the advantages that the method is only based on random response signals, operation is simple, the calculation amount is small, and identification accuracy is good.

The invention discloses a short-circuit current zero-point prediction method and a short-current current phase selection breaking control method. The short-current current phase selection breaking control method comprises: S1, a current signal is collected in real time and whether a short-circuit fault occurs is determined; if so, a S2 is executed; and if not, current signal collection is carried out continuously; S2, a short-circuit current is processed by using a similar-prony method to obtain a short-circuit current zero point; S3, according to the short-circuit current zero point, opening motion time of a circuit breaker, and optimal arcing time, delay time of a distance target phase is obtained; S4, whether a relay protection instruction arrives is determined; if so, switch breaking is carried out directly; and if not, delay counting down is carried out; S5, whether the delay counting time is zero is determined; if so, a S6 is carried out; and if not, counting down is carried out continuously; S6, after delay ends, whether a relay protection instruction reaches is determined again; if so, a S7 is carried out; and if not, the breaking operation is withdrawn; and S7, disconnecting of a circuit breaker is controlled and phase selection breaking is realized after the optimal arcing time.

A node phase relation identification method of an electric system based on a wide area measurement noise signal belongs to the technical field of stability analysis of the electric system. The method is characterized by comprising the steps of injecting small-amplitude random disturbing time sequences at the load position of the electric system, measuring the response time sequence signals of the system, identifying the frequency and damping ratio parameter of a low-frequency oscillation mode by using an autoregressive moving average (ARMA) model, further using a Prony method to estimate the phase information of the node in the low-frequency oscillation mode based on the obtained information of the low-frequency oscillation mode, and synchronously collecting the system responses, namely noise-like signals of a plurality of nodes according to the same steps, and analyzing the phase information of each node in the low-frequency oscillation mode, and finally calculating to obtain the inter-node phase relation in the same low-frequency oscillation mode. The invention is capable of correctly analyzing the dynamic characteristics of the prior system in time under the condition that the system normally runs.

According to the invention, a controlled or synchronous switching of an electrical power breaker (1) can be guaranteed by means of predicting a future voltage and / or current curve from actual voltage and / or current data in an electrical energy network (5). The prediction of the future voltage and / or current curve is carried out using the voltage and / or current data determined in the electrical network (5) at different timepoints by application of a Prony method to the available voltage and / or current data.

The invention belongs to the technical field of channel prediction, and discloses a prediction method, a prediction system and an application based on a multi-order channel. The method comprises the steps of determining a channel model, popularizing a classical Prony method into a vector form, and propose an algorithm 1; and predicting a future channel vector through the algorithm 1 and by using an acquired channel vector sample. Aiming at the actual challenge-mobility problem of Massive MIMO, the invention provides the prediction method based on the multi-order channel, and the error-free channel prediction can be approximated when the known channel sample is accurate enough. If the known channel sample is inaccurate, the sample precision is improved based on a sub-space structure and thelong-term statistical information of the channel observation, so that the channel prediction precision can be improved. The method, the system and the application of the present invention can be applied to a 5G base station, or a future communication base station, and other wireless transmitting or receiving devices.

The invention belongs to the power grid electric energy metering technical field and relates to a method for adaptively calculating power under arbitrary frequencies. The method includes the following steps that: a sampling period is set as T, voltage signals and current signals of the load end of a power grid are synchronously sampled in a timed manner, so that voltage sampling data u (t) and current sampling data i (t) at the same time point can be obtained; operating condition matching analysis is performed on the voltage sampling data u (t) or current sampling data i (t), so that N alternating current components are obtained; and alternating current voltage u1, u2,..., uN, alternating current i1, i2,..., iN, and frequencies f1, f2,..., fN of the N alternating current components are obtained through fitting and by means of an improved extended Prony method, and the active power P1, P2,..., PN and passive power Q1, Q2,..., Q3 of each alternating current component are calculated out. With the method adopted, voltage signals and current signals can be decomposed into a plurality of harmonic components of which the frequencies, amplitudes and phases are known in real time under a condition that the harmonic of a power system is complex, in particular under a condition that non-integer-order harmonic exists or the content of harmonic is complex, and therefore, the power of the alternating current components of the load end of the power system can be measured accurately. The method has the advantages of simple implementation, high accuracy and easiness in realization.

The invention discloses an acoustic liner acoustic impedance measurement method under a condition of acoustic wave grazing incidence. The method includes the steps of installing an acoustic liner on a side wall of a sound transmitting tube having a rectangular cross section; obtaining wall sound pressure of the position where M measurement points are selected on an opposite side to the side wall where the acoustic liner is located; based on modal characteristics of sound propagation in a tube, enabling the wall sound pressure of the sound tube to be written in an exponential function superimposed form, so that the number of axial wave of sound propagation in the sound tube can be identified through a Prony method; then extracting acoustic impedance in two cases, an when the gas in the sound tube is uniform flow, obtaining the acoustic impedance simply by using a simple dispersion relation and an eigenvalue equation; and when the gas in the sound tube is shear flow, obtaining the acoustic impedance by using an impedance boundary condition after a Pridmore-Brown equation is numerically solved. The advantages of the invention lie in that compared with conventional extraction methods, the acoustic liner acoustic impedance measurement method greatly simplifies the extraction process, reduces the number of measurement points of the wall sound pressure, and is free from the influence of reflection from an outlet; and the invention provides a novel test method for the industry community.

The invention relates to a detection method of blood sugar concentration based on a neural network algorithm. The method includes the following steps that a human body earlobe model is made; test blood with different blood sugar concentrations is prepared; a first antenna is used to transmit an ultra wide band microwave signal, a second antenna receives the signal which penetrates the earlobe model; the obtained received signal is processed, signal characteristic poles including resonant frequencies and attenuation factors are extracted by a Prony method, eighteen characteristic poles of the received signal are extracted, wherein the number of the resonant frequencies is nine, the number of the attenuation factors is nine, a total of eighteen signal characteristic poles is as a group; anda BP neural network is selected to train.

The invention provides a system damping on-line monitoring method based on traction load impact response. The method includes the steps: firstly, obtaining actual oscillation modes of main intervals of a power grid and strong correlation set information of the modes; secondly, selecting a set that is close to a traction load electrical distance and is a strong correlation set of a main interval mode and making the set serve as a monitoring node on the basis of geographical distribution of traction loads in the power grid and zone division of the oscillation modes of the power grid intervals; thirdly, on the basis of monitoring node dynamic measurement, for a set that enables a person to observe obvious oscillation response under the traction load impact, adopting a Prony method to identify on-line the system interval oscillation frequency and damping ratio information; fourthly, for a set that enables a person not to observe obvious oscillation response under the traction load impact, adopting an ARMA method to analyze set active power noise like signals and obtain real-time oscillation frequency and damping information; and fifthly, emitting alarming information in a grading manner by responding to a condition that the system real-time mode damping ratio is lower than a given threshold.

The invention discloses a DOA estimation algorithm based on Prony method. The algorithm is suitable for estimating the target azimuth in radar and sonar systems, and is characterized by comprising the following steps that: step 1, the DOA estimation algorithm measurement equation is obtained; step 2, for the uniform linear array, the Prony method is used directly to solve the measurement equation; step 3, for the uniform circular array, the transformation matrix is constructed, and then the measurement equation is solved by Prony method. The technical scheme of the DOA estimation algorithm based on Prony method realizes the target DOA estimation in measuring a platform of the uniform linear array and the uniform circular array, and the estimator performs well under high signal-to-noise ratio condition, no search is required, and the computational complexity is reduced without the feature decomposition. At the same time, the DOA estimation algorithm can break through the Rayleigh limit of the array, and the resolution is higher; moreover, the decoherent operation is not needed under the condition of coherent source, which provides a new method for DOA estimation algorithm.

The invention relates to a fault voting line selection method by using Prony relative entropy. The method comprises that when a bus zero sequence voltage instantaneous value is 0.15 times larger than a nominal voltage, a fault line section device is immediately started, a Prony method is adopted for matching a transient state zero sequence current signal in a first T / 4 cycle of each branch circuit after a fault; transient state dominant component of superficial characteristics fault characteristic information is selected according to a amplitude maximum principle; and then, transient state dominant component relative entropy of each branch circuit relative to other branch circuits is obtained; and finally, the fault voting line selection mechanism adopting preliminary voting, k value checkout, and final voting are put forward to vote for each branch circuit, so that a faulty line is selected. Theoretical analysis and a large number of simulations indicate that fault voting line selection method can effectively avoid influence of current transformer flux density saturation to line selection, and can greatly improve reliability of fault line selection results.

The present invention discloses a Givens iteration based Prony analysis method for low frequency oscillation, and the analysis method adopts an iterative method to reduce the number of orders of a signal model, and improve numerical stability of calculating a characteristic equation coefficient to solve an equation set. The method comprises the following steps: reading measurement data after filtering; using a singular value decomposition method to calculate the actual number of orders of the signal model; using a Givens iterative method to calculate the characteristic equation coefficient; calculating frequency and an attenuation factor; and calculating amplitude and an initial phase. According to the method disclosed by the present invention, by using a Givens iterative Prony method to analyze low frequency oscillation, the number of orders of the signal model maybe the actual number of orders of the signal model during extended Prony analysis, so that the singular of a coefficient matrix for using the characteristic equation coefficient to solve the equation set is effectively avoided, and the numerical calculation stability is improved; and under conditions of the number of orders of the signal model is the actual number of orders of the signal model, the method disclosed by the present invention has a higher calculated result of low frequency oscillation information than the result calculated by using the conventional Prony method.

The invention relates to a method for conducting multi-modal dynamic equivalence on complex electrical power systems except for generators. The method comprises the steps of S1 enabling an external system of a generator set to be studied to be equivalent to a parallel system of an infinite bus and N dynamic units, wherein the infinite bus is expressed as (a formula), and the N dynamic units are expressed as (a formula), S2 in a steady state condition, conducting load flow calculation or on-line measurement to obtain an initial steady-state value of a system, S3 exerting disturbance, recording obtained response quantity, S4 adopting spectral analysis or the prony method to analyze the number N of modals of significant variables at the end of the generator set to be studied, determining the total number N of dynamic equivalence units, S5 according to a multi-modal equivalent model, using data to select an appropriate identification method to identify parameters required to be equaled, and obtaining the dynamic equivalence result. The method better reflects dynamic characteristics of the external system of the generator set to be studied and improves accuracy of optimization design of an excitation controller.

The present invention discloses an uncertain factor identification method at operation of a microgrid. The uncertain factor identification method comprises the steps of utilizing the fault disturbancedata of the microgrid (group) grid-connected access points to extract the uncertain factor characteristics of the microgrid, wherein the characteristic information contains the information of the uncertain factors, such as the frequency, the amplitudes, the attenuation coefficients, the phases, etc., and adopting an extension Prony method to identify the uncertain factors. The uncertain factor identification method of the present invention utilizes a characteristic mode of the disturbance data to describe the dynamic characteristics of the uncertain factors, and determines a microgrid grid-connected planning and simulation model on the condition of not needing to specify the topological structure and the operation parameter of the microgrid.

The invention discloses a residual iteration Prony low frequency oscillation analysis method. An iteration method is adopted to reduce the order of a signal model and improve the numerical stability for resolving a characteristic equation coefficient solving equation set. The analysis method specifically comprises the following steps: reading in measured data after filtering; calculating the actual order of the signal model by using a singular value decomposition method; calculating characteristic equation coefficients by using a residual iteration method; calculating frequency and attenuation factors; calculating amplitude and an initial phase; according to the residual iteration Prony low frequency oscillation analysis method, low frequency oscillation is analyzed through a residual iteration Prony method, so the order of the signal model during expanding Prony analysis can be reduced, and the numerical stability for resolving the characteristic equation coefficient solving equation set is improved. Under the condition that selected signal model orders m are the same, the result accuracy of low frequency oscillation information calculated through the method provided by the invention is higher than that of a traditional Prony method.

The invention discloses a low-frequency oscillation identification method and suppression method of a generator excitation system. The method comprises the following steps: an AC component pre-estimation function is established and converted into a normal equation set, and SVD decomposition is carried out on a coefficient matrix to obtain k singular values; then, the Frobenious norms of k singularvalues are solved; an effective data order m of the active power of the lower generator excitation system is determined to solve an estimation function coefficient of the AC component estimation function according to the effective data order m; parameters b1, b2,..., bm are calculated, an attenuation factor di, a phase theta i, an oscillation frequency fi and an oscillation amplitude Ai with theorder of m are calculated by using the parameters according to the Prony method, so that the low-frequency oscillation mode of the generator excitation system at the current sampling moment and in N previous sampling moments can be identified. Moreover, the method can achieve the advanced intervention of the output quantity of the PSS model, and achieves the inhibition of the low-frequency oscillation of the generator excitation system in an advanced control mode.

The invention provides an imbalanced signal extracting method of a dual-rotor system with slight speed difference, and aims to solve the problem of difficultly in extracting imbalanced signals of the system in the prior art. With regard to un-damped real-value sinusoid signals, an improved Prony method (IPM for short) can be adopted to rather precisely estimate the frequency of each sinusoid signal. For the characteristics of beat vibration signals in the dual-rotor system with slight speed difference4, a band-pass tracking filtering method is adopted to reduce noise and then samples are extracted from filtered data, the IPM is adopted to realize frequency identification of two adjacent frequency signals; and then a least square method is used for identifying the amplitude and the phase of the beat vibration signals.

The invention belongs to the field of array signal processing.To propose a super-resolution DOA estimation technical scheme of a far-field narrow-band information source,according to anatomic norm mutual coupling DOA estimation method based on an auxiliary array element, by analyzing the Toeplitz structure of a mutual coupling coefficient matrix MCM without an auxiliary array element, aconstruction selection matrix is constructed in a symmetrical manner to intercept received data, so that remaining data has cyclic mutual coupling coefficients; by including unknown mutual coupling coefficientsinto an information source part, a new steering vector of the intercepted data is obtained; the ANM framework is minimized according to an atomic norm, semi-definite programming (SDP) solution of a mutual coupling DOA estimation model is conducted, and the Prony method describing equally spaced sampling data is used for estimatingfrequency components included in x(t),and then the estimation of direction of arrival of the input far-field narrow-band information source is completed based on the corresponding relationship between frequency f and incident angle theta. The atomic norm mutual coupling DOA estimation method based on the auxiliary array element is mainly applied to array signal processing situations.

The embodiment of the invention provides a high-frequency resolution harmonic and inter-harmonic Prony method and device. The method comprises the steps that according to a sampled electric power system signal, an autocorrelation matrix is constructed, and characteristic decomposition is conducted on the autocorrelation matrix to obtain autocorrelation matrixes represented by corresponding featurevectors; a first Prony coefficient is obtained on the basis of a subspace method and the symmetry of the first Prony coefficient according to the feature vectors and the sine wave number in the electric power system signal; and the damping factor and the frequency of each component in the electric power system signal are obtained according to the first Prony coefficient. According to the high-frequency resolution harmonic and inter-harmonic Prony method and device, by utilizing the symmetry of the Prony coefficient and the advantages of the subspace method, the computing burden is greatly reduced, and the precision of high-frequency resolution harmonic and inter-harmonic analysis of an electric power system is improved.

The invention discloses a grounding parameter acquisition method based on an arbitrary layered soil Green function. Aiming at the two limitations of global equal-interval sampling and PRONY methods adopted by most layered soil green function calculation in current base parameter calculation, the method comprises the following steps: 1, the complex exponential term of the PRONY method is twice of the number of soil layers, and the calculated amount is linearly increased along with the number of soil layers; 2, key features of an integral kernel function cannot be effectively sampled through global equal-interval sampling; in order to solve the problem that a complex stratified soil model cannot be solved completely due to the fact that the complex stratified soil model cannot be solved completely, the invention provides an arbitrary stratified soil Green function calculation method for performing segmented sampling according to extreme points of an integral kernel function and fitting data points of segmented sampling in combination with a least square method by analyzing distribution characteristics of the integral kernel function. Compared with a PRONY method under global sampling, the method provided by the invention can better approach an integral kernel function, and has the advantages of high calculation efficiency, good precision and the like.

The invention discloses an output-based semi-submersible ocean platform energy transfer path analysis method, which comprises the following steps of: arranging acceleration sensors at a vibration source and a target point to form an array, performing characteristic component analysis on a signal at the vibration source by utilizing a short-time Prony method based on a state space model, and determining a characteristic frequency; dispersing signals at a vibration source and a target point, introducing a first-order matrix differential equation by utilizing a complex exponential decomposition technology, and extracting signals at a characteristic frequency; solving a correlation coefficient of the reconstructed signal near the characteristic frequency, and extracting a characteristic component; calculating the amplitude of the characteristic component, substituting the amplitude into a formula to solve the transmissibility, and drawing the transmissibility spatial distribution map spatially to obtain the change rule of the transmissibility of the characteristic signal component in the whole spatial range so as to reveal the characteristic signal transmission condition. The method only depends on output response signals obtained through testing, and measurement of exciting force and a transfer function in a traditional method is avoided.

The invention discloses a near-field signal source positioning method without gridding based on sparse reconstruction. The method specifically comprises the following steps: acquiring a covariance matrix based on a signal model received by a symmetric uniform linear array, extracting reverse diagonal elements of the covariance matrix, constructing a correlation matrix similar to a Toeplitz matrix,and constructing a target function based on a covariance fitting criterion; estimating a Toeplitz correlation matrix by using positive semidefinite programming, estimating the direction of arrival ofa near-field signal source by using a Prony method based on the Toeplitz correlation matrix, then using a conventional subspace-based method to effectively estimate the range, and using a MUSIC method to estimate the range constructing a correlation matrix similar to a Toeplitz matrix by reverse diagonal elements of the signal covariance matrix; establishing a convex optimization problem for reconstruction of the correlation matrix, and using the Prony method to estimate the direction of arrival of the near-field signal source based on the recovered correlation matrix, so that the problem ofhigh computational complexity caused by iterative operation is avoided, and the problem of grid mismatch of a traditional gridding method is avoided at the same time.

The invention discloses a subsynchronous oscillation analysis method based on EEMD and Prony methods, and belongs to the technical field of subsynchronous oscillation of power systems. The method comprises: firstly, using EEMD to decompose a noise-containing signal, removing a high-frequency noise component in the noise-containing signal, meanwhile, solving the modal mixing problem during EMD denoising, and after a stable signal is obtained, accurately recognizing characteristic parameters of subsynchronous oscillation through Prony. Centralized empirical mode decomposition (EEMD) denoising and Prony identification are combined so that the problem of modal superposition in EMD is effectively solved; because the Prony method is sensitive to noise signals, the result of the denoised signalsis more accurate by using Prony identification, the dominant mode of subsynchronous oscillation can be identified, the method is crucial for analyzing the source of oscillation and proposing inhibition measures, and the method has the advantages of strong noise immunity and high accuracy.

The invention belongs to the impedance spectrum measurement technological field and relates to a Prony state space algorithm-based impedance spectrum measurement method and tester. According to the Prony state space algorithm-based impedance spectrum measurement method and tester, a state space equation is introduced into an algorithm, so that the problem of solving a higher-order function in a traditional Prony method is solved, and therefore, the method, capable of replacing a Fourier method, can be applied to practical engineering; and the method can obtain an accurate impedance spectrum byusing test signals obtained in a short time in one-time measurement, can avoid the problems of frequency leakage and frequency mixing, and has an excellent noise cancellation effect.

The invention relates to a method for identifying modal parameters of an oscillation signal. The method comprises the following steps: acquiring an original signal of a system, processing the original signal through an empirical mode decomposition method, extracting an intrinsic mode component, and constructing a new signal; processing the new signal by using a random subspace identification method to obtain the frequency and damping ratio of the system; processing the new signal by adopting a Prony method to obtain the frequency, the amplitude and the phase angle of the system; and on the basis of the same frequency rule, pairing the modal parameters obtained by the random subspace identification method and the Prony method to obtain complete and accurate modal parameters. Compared with the prior art, the method has the advantages that the oscillation signal is subjected to stabilization processing by using the empirical mode decomposition method, the sensitivity of the Prony algorithm to noise is overcome, the false mode generated by the random subspace algorithm in processing nonlinear and non-stable signals is avoided, the mode identification is performed by fusing the random subspace identification method and the Prony method, and the mode parameter identification precision is improved.

The invention provides a downlink time-varying channel prediction method based on an improved Prony method. The downlink time-varying channel prediction method is applied to a time division duplex system, and the downlink time-varying channel prediction method comprises the following steps: S1, estimating the CSI of an uplink: assuming that the bit error rate of the uplink system is known, obtaining decoded data symbols by a base station, and estimating the CSI of the uplink according to received signals and the decoded data symbols; S2, calculating a Prony coefficient according to the estimated uplink CSI; S3, predicting the CSI at the next moment according to the Prony coefficient and designing precoding; a base station in the TDD system being provided with Mb antennas, for a single userwith a single antenna, the number of clusters being Lc, each cluster being provided with a main path, and a communication system starting from an uplink. The method can be suitable for estimating thefast time-varying channel, can accurately predict the CSI of the downlink at the future moment, and can greatly improve the overall performance of a communication system.

The invention belongs to the technical field of non-intrusive load monitoring, and particularly relates to an electric appliance fingerprint feature extraction method based on different Prony methods. According to the method, some characteristic quantities showing unique characteristics during operation of the equipment are used as electric appliance fingerprints of the equipment and are used for describing different modes shown by current or voltage waveforms and the like of the equipment. Aggregated load information obtained aiming at non-intrusive load monitoring is extracted, five Prony methods are adopted to carry out electric appliance fingerprint extraction, so that transient (exponential damping) and steady-state (harmonic information) characteristics of circuit loads are obtained, and the electric appliance fingerprint of each load is separated by adopting a load decomposition means; and individual energy consumption of devices connected to a certain power bus is determined, and a change in electrical energy at a single point of the bus is measured. According to the invention, circuit load information can be better processed, and better energy scheduling and management of equipment in the circuit can be realized.

The invention provides a system damping online monitoring method based on a capacitor switching response, which comprises steps: 1, actual main inter-area oscillation modes of a power grid and unit information strongly related to each mode are acquired; 2, according to the geographical distribution of main capacitors and key units in the power grid and the power grid inter-area oscillation mode area division, a unit which has a close electrical distance with a switching capacitor and is from units strongly related to the main inter-area modes is selected as a monitoring node; 3, based on dynamic measurement of the monitoring node, as for a unit whose oscillation response can be obviously observed under the capacitor switching impact, a Prony method is adopted to online recognize the system inter-area oscillation frequency and damping ratio information; 4, as for a unit whose oscillation can not be obviously observed under the capacitor switching impact, an ARMA method is adopted to analyze unit active power noise signals to acquire the real-time oscillation frequency and damping information; and 5, in response to a case when the system real-time mode damping ratio is lower than a given threshold, warning information is sent in different grades.