Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for classifying electric energy quality mixing disturbances based on multi-feature quantity of time-frequency domain

A power quality disturbance, multi-feature technology, applied in instruments, character and pattern recognition, computer parts and other directions, can solve problems such as mutual influence and complex signal characteristics

Inactive Publication Date: 2012-12-19
SOUTHWEST JIAOTONG UNIV
View PDF2 Cites 36 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Considering that the signal characteristics of the power quality mixed disturbance are very complex, and there are mutual influences among various single disturbances, etc.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for classifying electric energy quality mixing disturbances based on multi-feature quantity of time-frequency domain
  • Method for classifying electric energy quality mixing disturbances based on multi-feature quantity of time-frequency domain
  • Method for classifying electric energy quality mixing disturbances based on multi-feature quantity of time-frequency domain

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0090] figure 1 It is the overall algorithm flow chart of the present invention.

[0091] A. Generation of original data of power quality mixed disturbance

[0092] Since the actual sampling signal cannot fully reflect the diversity of disturbance signals, MATLAB software is used to randomly generate normal signals, sags, swells, short-time interruptions, pulse transients, oscillation transients, harmonics and flicker. Single disturbances and 40 mixed disturbances.

[0093] Each type randomly generates 50 samples, the signal fundamental frequency is 50Hz, and the signal sampling frequency is 3.2kHz. All signals are superimposed with Gaussian white noise with a signal-to-noise ratio of 40dB.

[0094] B. Feature quantity construction and extraction

[0095] Time-Frequency Domain Analysis of Power Quality Mixed Disturbance Signals: Using EEMD and MIST ( figure 2 ) after processing the signal, 9 time-frequency domain feature quantities suitable for mixed disturbance classifi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for classifying electric energy quality mixed disturbances based on multi-feature quantity of time-frequency domain. Voltage dip, voltage swell, short-term voltage interruption, impulsive transient, oscillatory transient, harmonic waves and flickering electric energy quality disturbances and mixed disturbances of a combination thereof are classified. The method for classifying the electric energy quality mixed disturbances concretely comprises the steps of: firstly, processing a disturbance signal by using an EEMD (Ensemble Empirical Mode Decomposition) and MIST (modified incomplete S-transform), and extracting nine time-frequency domain characteristic values; and then, inputting characteristic quantity to a blocked automatic classifying system to recognize the disturbances. By using the method, the mutual interference among single disturbances is fully considered and is effectively inhibited through the complementary time-frequency domain characteristic values. A simulation result shows that, under conditions of certain noises, the method can be used for effectively classifying the voltage dip, the voltage swell, the short-term voltage interruption, the impulsive transient, the oscillatory transient, the harmonic waves and the flickering electric energy quality disturbances and the mixed disturbances of the combination thereof.

Description

technical field [0001] The invention relates to a new method for classifying power quality mixed disturbances based on time-frequency domain multi-feature quantities. Background technique [0002] In recent years, power quality issues have received widespread attention from all walks of life. In-depth study of various factors affecting power quality, accurate extraction of power quality disturbance signal characteristics, and correct classification of power quality disturbances are the premise and basis for power quality analysis and evaluation. [0003] So far, a large number of scholars at home and abroad have studied the classification of power quality and achieved certain results. However, in actual power systems, power quality disturbances are often mixed disturbances, and multiple disturbances may exist at the same time. Most of the existing power quality disturbance classification methods are for the classification of single disturbances, and it is difficult to solv...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
Inventor 刘志刚张杨张桂南张巧革
Owner SOUTHWEST JIAOTONG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products