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A Method for Acquiring Dynamic Signal Parameters

A technology of dynamic signal parameters and acquisition methods, applied in spectral analysis/Fourier analysis and other directions, which can solve problems such as difficulty and poor numerical stability

Active Publication Date: 2015-09-30
STATE GRID CORP OF CHINA +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, directly solving the amplitude, phase frequency and attenuation factor parameters in the Prony algorithm will lead to solving a nonlinear least squares problem, which is difficult and has poor numerical stability

Method used

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  • A Method for Acquiring Dynamic Signal Parameters
  • A Method for Acquiring Dynamic Signal Parameters
  • A Method for Acquiring Dynamic Signal Parameters

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 2

[0070] In this embodiment, we introduce the process of determining the number of frequency components of the dynamic signal in detail.

[0071] Through Example 1, we have determined the autocorrelation matrix R e , and then the SVD algorithm can be applied to determine the matrix R e The effective rank P, and then determine the number of dynamic signal frequency components through the effective rank P, specifically the autocorrelation matrix R e Decomposed into:

[0072] R e =USV T (3)

[0073] where R e represents the autocorrelation matrix, U is p e ×p e dimensional orthogonal matrix, V is (p e +1)×(p e +1) dimensional orthogonal matrix, S is p e ×(p e +1)-dimensional non-negative diagonal matrix, the elements on its diagonal σ kk is the matrix R e singular value of , and satisfies It can be seen that the matrix R e Larger singular values ​​are concentrated in the front section of the diagonal matrix S, so the diagonal matrix Σ composed of the first ...

Embodiment 3

[0087] In this embodiment, we introduce the process of determining the parameters of the dynamic signal model in detail.

[0088] The AR model is established. The AR model assumes that the signal x(n) is obtained by exciting a linear time-invariant discrete-time system with all poles by the zero-mean white noise sequence w(n), namely:

[0089] x ( n ) = - Σ k = 1 C a k x ( n - k ) + w ( n ) - - - ( 5 )

[0090] In the above formula, C is the order of the model, a k is the model parameter of the C-order AR model.

[0091] According to the effe...

Embodiment 4

[0097] In this embodiment, we introduce the parameter determination process of the dynamic signal in detail.

[0098] Using the Prony algorithm, the signal x(n) is regarded as composed of a group of sinusoidal components of decaying oscillations, namely:

[0099] x ( n ) = Σ i = 1 q A i e α i n T s cos ( 2 π f i n T s + θ i ) - - - ( 6 )

...

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Abstract

A dynamic signal parameter acquisition method comprises: selecting a dynamic sampling signal sequence of a power grid to form an autocorrelation matrix (101); determining an effective rank of the autocorrelation matrix and frequency components of the dynamic sampling signal sequence (102); establishing an auto-regressive (AR) model, and resolving a model parameter of the AR model (103); expressing the dynamic sampling signal sequence as a set of attenuated oscillating sinusoidal components using a Prony algorithm (104); determining a complex sequence of the dynamic sampling signal sequence, the dynamic sampling signal sequence being expressed by the complex sequence under a condition of minimum square error (105); and introducing a root of a characteristic polynomial corresponding to the model parameter into the complex sequence, and resolving various parameters of the dynamic sampling signal sequence, the various parameters including the amplitude, the phase, the attenuation and the frequency (106). Instead of directly resolving parameters in the Prony algorithm, the method regards a current signal as a linear combination of each previous signal through AR parameter model method, and converts a nonlinear problem into a linear estimation problem, so that the computing process is simpler and the computing result is more accurate.

Description

technical field [0001] The present application relates to the technical field of power grid harmonic analysis, and more specifically, to a method for acquiring dynamic signal parameters. Background technique [0002] Due to the wide application of nonlinear devices such as power electronics in the power system, not only the harmonics and interharmonics are increasing, but also there are attenuating oscillation components, which seriously affect the safe operation of the power system. The analysis of harmonics, interharmonics and damped oscillation parameters is of great significance to power systems. [0003] The current harmonic analysis mainly adopts the Fourier method, which regards the signal as composed of a series of non-attenuating sinusoidal frequency components, so it is impossible to give the attenuation oscillation parameters in the dynamic signal, and at the same time, the spectrum leakage and fence effect in the Fourier analysis are also It will cause the probl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R23/16
CPCG01R23/16
Inventor 欧习洋刘然侯兴哲郑可付志红胡晓锐张晓勇张淮清纪静吴华孙洪亮
Owner STATE GRID CORP OF CHINA