一种电能质量扰动检测的新方法。
提出了一种新的电能质量扰动识别与定位方法。
A novel approach on power quality disturbance detection is presented in this paper.
为此提出用短时李氏指数检测电能质量扰动的方法。
Therefore, and approach to the detection of power quality disturbance using short duration Lipschitz exponent is presented.
基于时域、多分辨率分析和规则基的电能质量扰动分类。
Power quality disturbance classification based on time domain, rule based and wavelet multi - resolution decomposition.
电力系统基波幅值、相位、频率扰动是最基本的电能质量扰动。
Amplitude deviation, frequency deviation and phase deviation are basic power quality disturbances.
最后，结合数据流技术对电能质量扰动的在线识别进行了研究。
Finally, combining data stream technology, on-line disturbance classification is completed.
提出了一种基于S变换和扩张神经网络的电能质量扰动分类方法。
A new approach combining S-transform and Extension Neural Network (ENN) to classify power quality disturbances is proposed in this paper.
该文方法为动态电能质量扰动的检测、识别与分类提供了新的思路。
The new method gives a entirely new way for detection, identification and classification of dynamic power quality disturbances.
近年来，电能质量扰动检测与识别已经成为众多领域普遍关注的问题。
In recent years, power quality disturbances detection and classification has become a problem which attracts the concern in many fields.
提出了一种对电能质量扰动进行检测、定位、辨识与分类的有效方法。
An effective method to detect, localize, identify, and classify power quality disturbance is proposed.
对电能质量扰动检测的研究逐步成为现代电力系统中重要研究课题之一。
Power quality disturbances detection is becoming one of the most important subjects in modern power system.
提出了电能质量扰动的专家概率分类器模型，用于常见电能质量扰动的分类。
An expert based probability classification model is employed to investigate generic power quality disturbances.
对各种电能质量扰动现象进行分析，是采取适当措施降低扰动带来影响的前提。
The identification and classification of disturbance is the premise to depress the wicked influences produced by them.
同时，文中还对目前尚未解决的复合电能质量扰动分类问题进行了初步的探讨。
Furthermore, classification of complex power quality disturbances which has not been resolved is discussed in the thesis.
有效地检测电能质量扰动，对于治理和改善电力系统的电能质量具有重要意义。
It is very important to find out the power quality disturbance in order to improve power quality.
该方法利用小波和小波包各自的时频分解特点，实现了暂态电能质量扰动的自动检测和分类。
Using the different time-frequency characteristics of wavelet and wavelet packet, the proposed approach can avoid the noise and complete the detection and classification of transient power quality.
利用所构造的复数正交紧支对称小波，分别研究了电网电能质量扰动的检测、定位与分类问题。
From this, detection, location and classification of power quality's disturbances are analyzed respectively, by the symmetry complex compactly-supported orthonormal wavelet constructed.
针对电能质量扰动具有非稳态、突发性的特点，提出了一种电能质量短期扰动分类和检测的新方法。
Aimed at the characteristics of power quality disturbance, a new method is introduced for detecting. classifying and quantifying the short duration variations of power quality.
暂态电能质量会给敏感用户带来重大损失，因此，在最普遍情况下识别叠加的暂态电能质量扰动非常重要。
Transient power quality may cause severe loss to sensitive customers; therefore, it is very important to recognize overlapped transient power quality under general terms.
针对电能质量扰动信号的特性，本文采用小波变换对电力系统的高频、瞬时脉冲、电压切痕扰动信号进行检测。
According to features of power quality disturbance signal, this paper detects the disturbance signals of high-frequency, transient impulse and voltage notch with wavelet transforming.
针对传统线性滤波器在暂态电能质量扰动检测中存在的固有缺陷，本文采用形态滤波器对电力扰动信号进行消噪。
Against the inherent defects of the traditional linear filter in the detection of transient power quality disturbances, this paper USES mathematical morphology morphological filters.
通过该方法可以确定非平稳的电能质量扰动信号的时间、频率和幅值信息；同样也可以精确的检测出谐波的幅值和频率。
It can detect time, amplitude and frequency of the power quality disturbances and also detect amplitude and frequency of harmonics by this method.
电能质量扰动主要包括谐波、电压暂降、电压暂升、电压中断、电压波动、暂态振荡、谐波暂升和谐波暂降等电能质量问题。
Power quality disturbances mainly include harmonics, voltage sags, voltage swells, voltage interrupts, flickers, oscillation transients, voltage sags with harmonic and voltage swells with harmonic.
随着各种敏感电力电子设备在工业中的广泛应用，诸如短时低电压、短时过电压等电能质量扰动问题已成为近年来各方面关注的焦点。
With the wide application of sensitive power electronic devices in industry, the power quality disturbance problems such as voltage sag and swell become more concerned.
算例分析表明，该算法不仅可实现配电网络中电能质量扰动源的自动、精确定位，而且具有简洁直观、计算量小、适于计算机编程实现等优点。
The proposed algorithm is simple and suitable for programming with low computational load, and case study shows that it locates the PQD sources automatically and accurately.
暂态电能质量问题日益突出，电容器投切造成的暂态扰动是其中较为常见的一种。
The transient power quality problems become more important. Capacitor switching which brings transient disturbance is a common power quality event.
分析表明，通过上述五项指标可以有效地提取不同扰动的特性，为电能质量分析提供新思路。
Analysis results showed that by these five indices, features of different disturbances can be extracted effectively. The proposed approach provides a new idea for power quality analysis.
分析和仿真结果表明该方法可以有效识别不同的扰动类型，为电能质量问题的改善措施提供依据。
Numerical results show that the method proposed can effectively classify different disturbance patterns and provide basis for power quality mitigation measures.
对于短时低电压扰动发生、恢复时刻的检测与定位则是电能质量监测和统计中获取相关指标首先要解决的问题。
The detection and location of the start point and end point of the voltage sag and swell is a key problem for the power quality monitoring.
对于短时低电压扰动发生、恢复时刻的检测与定位则是电能质量监测和统计中获取相关指标首先要解决的问题。
The detection and location of the start point and end point of the voltage sag and swell is a key problem for the power quality monitoring.
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