21 results about "Vector fitting" patented technology

The invention relates to the technical field of artificial intelligence analysis and optimization of a power system, and discloses a line loss variable separation method, system and device based on dynamic time sequence vector fitting, and a medium, and the method comprises the steps: fusing multi-source heterogeneous data, and constructing an enhanced feature vector sequence through an attention mechanism and a physical equation constraint; establishing a time-varying causal graph model based on a dynamic Bayesian network, introducing an attention mechanism to calculate time sequence feature similarity, calculating time-varying causal strength in combination with physical constraint loss and topological distance, and deducing dynamic causal; a theoretical line loss curve is dynamically fitted in a physical-data double-track modeling mode, and key nodes in a causal graph model are used as correction factors; the contribution degree of each factor to the line loss difference is quantified based on a Shapley value algorithm, and accurate separation and attribution of line loss components are realized.

The application discloses a macro modeling method for ensuring direct current precision, and the method comprises the following steps: reading n-port network parameters; initializing sampling points for constructing a macro model; initializing the order of the macro model; initializing the pole of the macro model; establishing a weighted linear system according to the current order, the sampling points and the pole; solving a linear equation set, judging convergence according to an error, and obtaining the macro model; and outputting the optimized macro model by applying a residue matrix disturbance to optimize the macro model. The macro modeling method for ensuring direct current precision provided by the application controls the direct current precision in two stages. In the first stage, a weighted least square method is adopted on the basis of a linear system established by a traditional vector fitting algorithm to preliminarily control the direct current precision. In the second stage, a small disturbance is applied to the residue matrix of the macro model, so that the disturbed macro model has accurate direct current characteristics.

The invention provides a parametric modeling method and device for a silicon-based millimeter wave on-chip component, and belongs to the technical field of integrated circuit modeling and millimeter wave circuit design. The method comprises the following steps: under a preset key parameter interpolation node, acquiring a transmission parameter of a de-embedding test structural member comprising a de-embedded component at each test frequency point; removing a parasitic effect embedded in the test structural member by using transmission matrix operation so as to obtain a transmission matrix of the de-embedded component and obtain a scattering parameter of the de-embedded component; then, through a vector fitting algorithm, obtaining a pole-residue model of the de-embedded component under the parameter interpolation node; and based on the pole-residue model under each parameter interpolation node, establishing a parameterized de-embedding model of the de-embedded component through a gravity center interpolation algorithm. According to the method, rapid and accurate modeling of silicon-based millimeter wave on-chip components of any size can be realized, and the reliability and efficiency of millimeter wave integrated circuit design are improved.

The invention discloses a neural network electromagnetic performance prediction method with causality and passivity constraints, and the method comprises the steps: obtaining geometric design variables of a TSV structure to be detected, inputting the geometric design variables into a trained electromagnetic performance prediction model, and obtaining the prediction values of a plurality of scattering coefficients of the TSV structure to be detected; wherein the electromagnetic performance prediction model comprises a polar point sub-network, a residue sub-network and a prediction sub-network, and the polar point sub-network and the residue sub-network are respectively used for determining a to-be-detected polar point vector and a to-be-detected residue vector corresponding to each scattering coefficient according to geometric design variables of a to-be-detected TSV structure; the prediction sub-network is used for determining a prediction value of a scattering coefficient of a corresponding type according to a to-be-measured pole vector and a to-be-measured residue vector; the electromagnetic performance prediction model is trained through a sample pole vector and a sample residue vector, and the sample pole vector and the sample residue vector are obtained by processing a sample scattering coefficient based on a vector fitting technology. The method is low in implementation cost and good in adaptability.

The invention discloses an S parameter time domain modeling method, device, medium and system based on vector fitting, and belongs to the field of microwave radio frequency device modeling and emulation.The method comprises the steps that a frequency domain response function is constructed based on a device S parameter, a residue and a pole value are approximated step by step through iterative optimization and a least square solution method, and the frequency domain response function is obtained; and finally, carrying out time domain convolution on the input signal based on the transfer function, and carrying out conversion of the output signal through the time domain convolution. According to the method, the simulation efficiency of the broadband microwave array system link time domain signal flow is improved.

The invention relates to a mechanism-data fusion new energy grid-connected system small interference stability analysis method. The method comprises the following steps: firstly, obtaining operation data of a new energy unit, and carrying out normalization preprocessing; then, a new energy unit impedance characteristic neural network model is constructed and trained, and a new energy field station impedance identification model is synthesized based on the trained unit impedance model in combination with the field station topology and the line parameters; then, on the basis of the new energy station impedance identification model, a vector fitting method and a PySR algorithm are adopted to construct an optimal fitting transfer function of the new energy station; then, determining a discrete state space equation based on the optimal fitting transfer function of the new energy station; and finally, calculating a discrete eigenvalue and a continuous eigenvalue of the system based on the discrete state space equation, and analyzing the stability of the system based on the discrete eigenvalue and the continuous eigenvalue. The online, continuous and accurate dynamic description of the impedance of the new energy unit and the dynamic stability prediction and analysis of a complex system are realized.

The invention discloses a new energy station broadband oscillation online early warning method based on a virtual split ratio, and belongs to the technical field of power system stability analysis and control. The method comprises the following steps: injecting a harmonic wave small disturbance signal into a current or voltage sampling value of a new energy converter, synchronously recording a static var generator (SVG) branch current waveform and extracting a disturbance component, and calculating a virtual shunt ratio; obtaining wide frequency band data through frequency sweeping, and obtaining a domain expression of a virtual split ratio through vector fitting; and solving the zero point of the expression to obtain a station characteristic root, and carrying out oscillation risk judgment and early warning according to the position of the station characteristic root on the complex plane. According to the method, control parameters and line parameters of the new energy converter in the station do not need to be obtained, a high-power disturbance source is not needed, the problems that an existing method is high in parameter dependence degree, modeling is difficult, and the calculated amount is large are solved, and rapid online early warning of the broadband oscillation risk in the full black box state of the new energy station is achieved.

The application relates to a passive property analysis method, device, equipment and medium in an S parameter modeling process. The method comprises the following steps: acquiring pole points and residue matrixes of S parameter vector fitting, each pole point corresponding to a residue matrix; constructing a new S parameter rational fraction based on the pole points and the residue matrixes; constructing a judgment matrix based on the pole points and the residue matrixes; constructing a plurality of detection frequency points according to the judgment matrix; and determining a passive abnormal frequency point based on the new S parameter rational fraction and the plurality of detection frequency points. When the passive property analysis is performed in the S parameter modeling process, the pole points and the residue matrixes of the S parameter vector fitting are considered to determine the passive abnormal frequency point, the frequency at which the passive property of the S parameter will be abnormal can be quickly determined, the violation degree of the frequency point in which the passive property is seriously violated is given, the high-cost calculation process of an original Hamiltonian is avoided, the calculation efficiency is improved, and the pressure of subsequent passive property correction is reduced.

The application discloses a new energy station wide frequency oscillation online early warning method based on a virtual shunt ratio, and belongs to the technical field of power system stability analysis and control. The method comprises the following steps: injecting a harmonic small disturbance signal into a current or voltage sampling value of a new energy converter, synchronously recording a static var generator (SVG) branch current waveform and extracting a disturbance component, and calculating a virtual shunt ratio; obtaining wide frequency band data through frequency sweeping and obtaining a domain expression of the virtual shunt ratio by using vector fitting; solving the zero point of the expression to obtain station characteristic roots, and judging and warning an oscillation risk according to the position of the characteristic roots on a complex plane. The application does not need to obtain control parameters and line parameters of the new energy converter in the station, and does not need a high-power disturbance source, thereby solving the problems of high parameter dependency, difficult modeling and large calculation amount of the existing method, and realizing rapid online early warning of the wide frequency oscillation risk in the full "black box" state of the new energy station.

The application provides a network parameter representation method based on a multi-path convolutional autoencoder. Network parameters are divided into network parameter real parts and network parameter imaginary parts. Each part is processed through N+1 paths, the first of which is a low-frequency path, and the remaining N paths are high-frequency compensation paths, each path processing different information of the network parameters. The network parameter representation method can avoid the residual-pole mismatch problem existing in the vector fitting method, has higher compression efficiency and higher accuracy, and can be used to establish a neural network proxy model and accelerate the design of microwave devices.

A method for multi-objective vector fitting includes the following steps: 1) processing a given dataset to construct a single-objective fitting dataset; 2) determining initial poles and using the initial poles and frequency sampling points to establish a fundamental matrix; 3) separating the real and imaginary parts of the fundamental matrix to construct a real fundamental matrix; 4) performing a simplified QR decomposition on the real fundamental matrix to obtain the first M columns of the complete Q matrix, denoted as Q. s Matrix, and for Q s The matrix is ​​stored; 5) Construct and solve the pole coefficient equation to obtain the pole coefficients; 6) Construct the pole characteristic equation using the pole coefficients and the initial poles to calculate the new poles; 7) Calculate the residues of each matrix element corresponding to the new poles to complete the vector fitting. This invention provides a method for multi-objective vector fitting that significantly reduces the computational complexity and improves computational efficiency.

The invention discloses a constraint vector fitting system and method fusing a shared pole structure and a local pole structure, designs a novel VF structure, introduces mixed pole configuration combining a shared pole and a local pole, and can maintain high-quality fitting of a Y parameter even in the presence of a loading phase. Therefore, the sensitivity of fitting precision to phase distortion is reduced; through post-processing identification of the model and iterative elimination of phase contributions corresponding to local poles and linear terms, compatibility with a traditional VF is ensured; in consideration of the characteristic that the VF mainly solves the residual error, the constraint on the number of transmission zeros is reconstructed into a group of linear constraints on the residual error, so that the problem can still be solved in the VF framework; in addition, a nonlinear residual constraint proposed in a physical realizability requirement is formalized into a nonlinear least square optimization problem to be introduced into a fitting process; the VF problem with physical constraints is solved by adopting an augmented Lagrange method ALM, and unified balance of fitting precision and physical consistency is realized.

The application provides a microwave filter shape-coupling relationship hybrid modeling method, device and storage device, constructs original data sets D1 and D2, extracts Y parameters y1 in D1 through a vector fitting method, constructs a data set Y1 containing resonance screw length x1 and Y parameters y1, extracts Y parameters y2 in D2, constructs a data set Y2 containing coupling screw length x2 and Y parameters y2, designs a microwave filter shape-coupling hybrid model, a shape-coupling relationship model in a serious detuning state and a shape-coupling relationship model in a slight detuning state, and realizes mapping from resonance screw length x1 and coupling screw length x2 to Y parameters y1 and y2. The application has the beneficial effects that the microwave filter is divided into two states of slight detuning and serious detuning, different structure geometric parameters are selected to establish shape-coupling relationship models, the complexity of establishing shape-coupling relationship models is reduced, and the accuracy of shape-coupling relationship models in various states is improved.

The invention discloses a positioning method for a performance abnormity problem of a three-dimensional heterogeneous integrated radio frequency circuit, and belongs to the field of integrated circuit design and manufacturing. The method comprises the following steps: firstly, carrying out electromagnetic field simulation on a circuit, carrying out joint simulation with an active device, obtaining a transfer function, and extracting poles through vector fitting; secondly, a variable parameter set representing physical attributes and geometric dimensions of the connection structure is defined, and small-amplitude disturbance is applied; then, calculating a sensitivity parameter set of poles based on disturbance, and further positioning a sensitive structure which has the most significant influence on the circuit performance according to sensitivity ranking; carrying out refined modeling on the sensitive structure; and finally, by comparing pole distribution and circuit performance change before and after refined modeling, realizing reason analysis of performance abnormality. According to the invention, the sensitive structure and the coupling path which cause electromagnetic performance problems such as high-frequency resonance and gain abnormity can be systematically and efficiently identified and positioned.

The invention provides a harmonic modeling method and system based on rotation coordinate transformation and vector fitting, and belongs to the field of power system analysis and modeling. The method comprises the steps of collecting three-phase voltage and three-phase current original data of a target node of the power distribution network, and performing preprocessing to obtain standardized voltage and current data; according to a preset rotation frequency set, performing rotation coordinate transformation on the standardized voltage data to obtain transformed voltage data; performing fast Fourier transform on the transformed voltage data and the standardized current data to obtain voltage frequency domain data and current frequency domain data; calculating a frequency domain admittance matrix according to the voltage and current frequency domain data to obtain frequency domain admittance data; fitting the frequency domain admittance data by adopting a vector fitting method to obtain a transfer function; and integrating all transfer functions in the rotation frequency set, and constructing a complete harmonic coupling admittance model. According to the method, the multi-frequency harmonic coupling characteristics can be accurately described, and the calculation efficiency is high.

The invention discloses a method and a device for analyzing a feasible region and optimizing the capacity of a converter of a network-following hybrid system, and belongs to the technical field of stability analysis of a power system. Comprising the following steps: constructing an impedance model of a GFL-GFM parallel system to obtain a closed-loop admittance matrix of the system; rational approximation is carried out on the closed-loop admittance matrix through vector fitting, and system characteristic values are extracted; according to the relation between the system characteristic value and the output power of different converters, the action direction and the action degree of the power of any converter on the system dominant characteristic value are obtained; discretizing a feasible region in combination with capacity constraint and power constraint, and solving the feasible region of the system; and on the basis of the obtained feasible region, quantifying the power grid strength of the system, and analyzing the change of the feasible region of the system by combining the power grid strength of the system and the change of the output power of the converter, thereby optimizing the capacity of the converter. According to the method, the calculation burden of feasible region solution can be reduced, and the capacity configuration and power distribution of the converter can be accurately guided.

The invention discloses an on-chip inductor high-frequency equivalent circuit establishing method, device and equipment and a medium, and relates to the technical field of semiconductors, in order to reduce the complexity of on-chip inductor high-frequency equivalent circuit modeling, the on-chip inductor high-frequency equivalent circuit establishing method comprises the following steps: on the basis of a test piece containing a radio frequency GSG PAD of a target inductor device, establishing an on-chip inductor high-frequency equivalent circuit; the method comprises the following steps: constructing three standard components containing a radio frequency GSG PAD; the test piece comprises an input GSG PAD, a target inductance device and an output GSG PAD; the standard component is constructed based on an input GSG PAD and an output GSG PAD; determining admittance parameters of the target inductor device based on the test data of the scattering parameters of the test piece and the test data of the scattering parameters of the three standard components; establishing a pole-residue model of the target inductor device according to the admittance parameters of the target inductor device in a vector fitting black box modeling mode; and according to the pole-residue model, constructing an on-chip high-frequency equivalent circuit of the target inductance device, and determining the value of each element in the on-chip high-frequency equivalent circuit.

The invention relates to the technical field of power system stability analysis, and particularly provides a stability analysis method for a multi-region new energy grid-connected system and electronic equipment, and the method comprises the steps: determining a first admittance matrix of a target region based on the power grid line data and new energy power generation data of the target region; second admittance matrixes of multiple target areas are calculated based on the first admittance matrix, and the multiple target areas are obtained by dividing the target areas according to measurement nodes of the new energy power generation data; performing vector fitting processing on all the second admittance matrixes to obtain a state-space equation corresponding to the new energy grid-connected system of the target region, and determining a pole of the state-space equation; and determining the stability of the new energy grid-connected system based on the position of the pole in the state space. The problem that it is difficult to give consideration to simple calculation and good real-time performance and accuracy when stability analysis of a multi-region and large-region new energy grid-connected system is carried out in the prior art is solved.

The application discloses a follow-up network hybrid system feasible region analysis and converter capacity optimization method and device, and belongs to the technical field of power system stability analysis. The method comprises the following steps: constructing an impedance model of a GFL-GFM coupled system to obtain a closed-loop admittance matrix of the system; performing rational approximation on the closed-loop admittance matrix through vector fitting to extract system eigenvalues; obtaining the action direction and action degree of power of any converter on the dominant eigenvalue of the system according to the relationship between the system eigenvalues and different converter output powers; combining capacity constraints and power constraints, discretizing the feasible region, and solving the system feasible region; on the basis of the obtained feasible region, quantifying the grid strength of the system, combining the grid strength of the system and the change of the converter output power, and analyzing the change of the system feasible region, so that the converter capacity is optimized. The application can reduce the calculation burden of the feasible region solving, and accurately guide the capacity configuration and power distribution of the converter.

The invention discloses a robot multi-target recognition and grabbing method and system based on boundary vector fitting, a storage medium and computer equipment, and the method comprises the steps: building a lightweight feature coding network and a dynamic region attention pyramid optimization module through a PyTorch deep learning framework; a U-shaped coding-decoding network model of multi-scale asymmetric jump connection is constructed; outputting a low-scale semantic mapping through the network model so as to search for a center point of a grabbed target and train four learnable boundary vectors; and fitting an object bounding box with rotation information by using the four boundary vectors, wherein the object bounding box is used for predicting the optimal grabbing classification and grabbing parameters of the object at the same time. By adopting the method, the problems of multi-target identification, classification and intelligent grabbing of mutually stacked, shielded and disordered objects in an unstructured scene can be solved.

The invention discloses a singularity processing method in S parameter vector fitting. The method comprises the following steps: determining an S parameter set needing to be fitted; determining the maximum number of iterations, the maximum number of effective iterations, the maximum pole and the maximum constant term; determining the initial pole number, the number of iterations and the effective number of iterations of vector fitting; carrying out vector fitting on a given S parameter, confirming the effectiveness of iteration according to an obtained new pole, and obtaining the number of effective iterations; and determining whether the vector fitting is successful or not according to the number of effective iterations. According to the singularity processing method in S parameter vector fitting, a reasonable vector fitting result can be given, so that subsequent passivity correction can be normally carried out, and a correct equivalent circuit can be generated.