电能质量扰动

基于dq变换和ANN的电能质量扰动辨识

Power quality disturbance identification using DQ conversion based neural classifier

幅度变化（AD）与相位变化（PD）是电能质量扰动的重要组成部分。

Amplitude deviation ( AD ) and phase deviation ( PD ) are the important compositions of power quality disturbance ( PQD ) .

基于GA与SVM的混合算法在电能质量扰动分类问题中的应用

Application of GA and SVM based hybrid algorithm for the classification of power-quality disturbances

电能质量扰动分类的改进stdMRA曲线分类法

Improved Std_MRA Curve Fitting Method for Classifying Power Quality Disturbance

利用时域均方根值电压变动特性、小波变换及FFT变换对多种电能质量扰动信号进行分层次辨识。

Using time-domain voltage-RMS , wavelet transform and FFT , various types of power quality disturbance signals are layered-recognized .

基于广义S变换和多级SVMs的动态电能质量扰动辨识方法研究

Study of Dynamic PQDs Identification Based on Generalized S-Transform and Multi-SVMs

基于Prony算法的暂态电能质量扰动信号分析

Transient Power Quality Disturbance Signal Analysis Based on the Prony Method

基于dq变换与小波变换的电能质量扰动检测与识别方法

Power quality disturbance detection and identification based on dq conversion and wavelet transform

本文借鉴经验模态分解（EMDEmpiricalmodedecomposition）方法的思想提出一种电能质量扰动快速定位的新方法三角模态检测方法。

In this paper , a new method based on the idea of EMD ( Empirical Mode Decomposition ) for the fast localization of power quality disturbances & Triangle Mode Method is presented .

针对电能质量扰动检测中存在的问题，提出一种基于Dyn测度的实时扰动检测方法。

A new power quality disturbances detection approach based on the Dynamics is proposed .

将该能量分布差向量作为所提取的信号特征向量，用于信号分类器输入，经三层BP神经网络得到电能质量扰动的类型。

Also , the energy distribution of a standard signal is calculated . The difference of the two energy distribution is used as the feature vector . A three-layer BP neural network is used as the classifier .

针对电能质量扰动信号特性，提出了一种基于Prony方法的信号分解算法。

A decomposition algorithm of analytic signal based on the Prony method was presented according to the power quality signal characteristic .

结果表明，Prony算法在暂态电能质量扰动信号分析中，可提供有效、准确的分析结果。

The satisfying results show the Prony method can provide effective and accurate results in the analysis of transient power quality .

提出了一种利用dq变换提取信号特征，并结合神经网络来识别电能质量扰动信号类型的方法。

This paper develops a method to detect and classify power quality disturbance waveforms using a novel combination of dq conversion and artificial neural networks .

在对电压信号进行小角度dq变换的基础上，提出了一种基于数学形态学的电能质量扰动检测与定位方法。

A new fast MM method based on small angle dq transformation is proposed to locate the disturbances of the voltage signals distorted by noise .

该改进PLL系统是一个稳定的相位反馈控制系统，产生的多个输出信号可用于多种电能质量扰动的检测，而且对于检测系统的内部参数和电力系统频率的变化是鲁棒的。

The PLL system is a stable phase feedback control system with many useful outputs , and it is robust to its inner parameters and small change of input 's basic frequency .

本论文主要探讨了电能质量扰动的检测与识别，提出了一种dq变换和小波变换相结合的方法，对常见的多种电能质量扰动进行检测与识别。

A method which uses dq transform and wavelet transform is put forward in this paper . It can detect and classify the familiar power quality disturbances effectively .

提出了一种基于S变换和多级支持向量机（SVMs）的电能质量扰动检测和识别方法。

A new method based on S-transform and multi-lay support vector machines ( SVMs ) is presented for power quality ( PQ ) disturbances detection and identification .

鉴于傅立叶变换优秀的幅频特性，小波变换优秀的时频特性和支持向量机优秀的统计学习能力，提出了基于FFT、小波变换和多类支持向量机的电能质量扰动识别方法。

After studying excellent amplitude-frequency characteristics of Fourier transform , and excellent time-frequency characteristics of wavelet transform and excellent statistical learning ability of SVM , the method in power quality disturbances recognition based on FFT , wavelet and SVM was created .

IST有优秀的时频分辨率特征并能准确地检测到扰动，因而，它很适合在噪声情况下的电能质量扰动的分析。

Improved S-transform is suitable for the analysis of power quality disturbances under noisy condition as it has excellent time-frequency resolution characteristics and has the ability to detect the disturbance correctly .

用于测试的电能质量扰动事件是受控参数随机产生的仿真算例，其数学模型均符合IEEE标准，可较全面的测试分类方法的有效性。

Power quality disturbance signals used for testing are all kinds of simulation examples containing random parameters , and their mathematical models meet the IEEE standard , so that the effectiveness of this method can be tested comprehensively . The process of the decision tree is clear .

基于ESTRO测量规程的加速器剂量参数测量与计算采用电量参数分析方法的电能质量扰动参数估计

The Method of Measuring Dose Parameters of LINAC Using ESTRO Rules ; Parameter Estimation Method of Power Quality Disturbances Based on Electrical Parameters Analysis

本文对7种主要电能质量扰动的检测、分析与辨识方法进行了研究，提出了基于ASW-ESPRIT算法的电能质量扰动分类辨识法，并设计和实现了电能质量扰动辨识系统。

In this paper , the detection , analysis and identification methods of seven kinds of main power quality disturbance are studied . Power quality disturbance identification based on ASW-ESPRIT algorithm is proposed to classify the power quality disturbance . It designs and implements the power quality disturbance identification system .

广义内插小波在电能质量扰动信号分析中应用

Application of generalized interpolating wavelet in power quality disturbance signal analysis

基于双尺度分形盒维数的电能质量扰动信号识别

Power quality disturbance analysis based on dual-scale fractal box counting dimension

基于数学形态学消噪的电能质量扰动检测方法

Detection of power quality disturbances based on mathematical morphology mm filter

基于短时网格分形维数的电能质量扰动检测

Detection of power quality disturbances based on short-duration grille fractal dimension

利用广义形态滤波与差分熵的电能质量扰动检测

Detection of Power Quality Disturbances Utilizing Generalized Morphological Filter and Difference-entropy

利用小波变换分析配电网电能质量扰动

Analysis of power quality disturbance in distribution network by wavelet transform

电能质量扰动检测与分类方法的应用策略

The Application Strategy for Power Quality Disturbance Detecting and Classification Method