Fault traveling wave detection method based on variational mode decomposition and S transform

Abstract

The invention discloses a fault traveling wave detection method based on VMD-S transform. The method comprises the steps of: S1: obtaining a fault traveling wave, and intercepting a traveling wave waveform of a certain time window, performing Karen Bell phase-mode transform, and extracting a line mode alpha component of the traveling wave; S2: performing variational modal decomposition (VMD) on the line mode alpha component to obtain K intrinsic mode functions (IMF), and then extracting the traveling wave waveform of an IMF1 component; S3: performing S transform on the IMF1 component to obtain a time-frequency distribution matrix of the waveform; S4: taking a module value of a matrix element to obtain an S mode matrix; and S5: extracting the first instantaneous frequency in the S mode transformation matrix obtained in the step S4, and calibrating a first amplitude sudden change point of the waveform to serve as an initial traveling wave front. The fault traveling wave detection methoddisclosed by the invention has the advantages of simple principle, high anti-interference ability, accurate calibration of the traveling wave head, and the like.

Description

technical field [0001] The invention mainly relates to the field of traveling wave detection, in particular to a fault traveling wave detection method based on variational mode decomposition and S transform. Background technique [0002] The distribution network is at the end of the power grid and is directly connected to the users. Due to the many branches of the distribution line, the low voltage level, and the complex operating environment, how to accurately identify the fault location and shorten the power outage time has become an important factor affecting the power supply reliability of the distribution network. Traveling wave location method has been widely concerned by scholars at home and abroad because of its characteristics of tolerance to fault types, transition resistance and system operation mode. [0003] The detection accuracy of the fault traveling wave head affects the accuracy of fault traveling wave location. The commonly used wavelet analysis has a good...

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Problems solved by technology

[0003] The detection accuracy of the fault traveling wave head affects the accuracy of fault traveling wave location. The commonly used wavelet analysis has a good effect on the detection of non-singular signals under certain noise conditions. Related, easy to produce different decomposition effects

EMD, the core empirical mode decomposition method of HHT transformation, will appear aliasing phenomenon and endpoint effect during the signal decomposition process, which will interfere with the extraction of signal mutations and cause large ranging errors

Although the Ensemble Empirical Mode Decomposition (EEMD) and Overall Local Mean Decomposition (ELMD) algorithms have improved the EMD algorithm for Empirical Mode Decomposition and reduced the aliasing phenomenon between the decomposition signals to a certain extent, they still can only suppress effect, cannot completely eliminate the impact of the decomposition method itself

The S-transform has good time-frequency resolution ability, and can extract the singular point of the frequency of the fault traveling wave signal. However, for the fault traveling wave signal under the strong noise interference of the distribution network, the ability of the S transform to distinguish the fault traveling wave signal is reduced, which is difficult to be effective. Distinguish the singular point of the fault traveling wave signal, making it difficult to accurately detect the arrival time of the fault traveling wave head

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