Voltage sag detection method for S-transformation on basis of time-frequency gathering characteristic criteria

Abstract

The invention discloses a voltage sag detection method for S-transformation on the basis of time-frequency gathering characteristic criteria. The method includes the first step of obtaining voltage sag disturbance signals to be detected generated in a power distribution network, the second step of conducting analog-digital conversion on an obtained voltage sag disturbance signal model, the third step of conducting optimized selection on gaussian time-frequency window width adjustment parameters in an improved S-transformation method according to time-frequency gathering characteristic criteria, substituting the gaussian time-frequency window width adjustment parameters selected according to empirical values, and conducting characteristic extraction, detection and analysis on digital signals to be detected in the second step through the improved S-transformation. Selection of condition parameters of a gaussian window function is optimized through the constraint condition that the value of a time-frequency gathering characteristic expression is maximized when the signals are analyzed through the improved S-transformation, and the improved S-transformation is applied to characteristic extraction, detection and analysis on voltage sags. The voltage sag detection method for S-transformation on the basis of time-frequency gathering characteristic criteria has the higher detection accuracy degree and signal denoising capacity on transient-state electric energy quality signals.

Description

technical field [0001] The invention relates to a voltage sag detection method based on time-frequency aggregation characteristic criterion S-transformation, which belongs to the field of transient power quality disturbance signal analysis, and is especially suitable for the extraction and detection of transient signal feature quantities when voltage sag occurs in distribution networks and analyse. Background technique [0002] In recent years, transient power quality disturbances such as voltage sags, swells, short-term interruptions, and transient oscillations to varying degrees have caused major problems in places such as airports, banks, precision electronic component manufacturing, computer networks, and service monitoring centers. economic loss. In order to take reasonable measures to control transient power quality problems, it is necessary to speed up the establishment of an effective power quality online monitoring system, and the first and most critical step is to...

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Problems solved by technology

[0004] The short-time Fourier transform always has inherent deficiencies in capturing abrupt signals such as fluctuations and harmonics: time positioning is inaccurate, all analysis scales are required to be roughly the same, and the discrete form of the transform is not orthogonally expanded, making it difficult to achieve efficient operations

However, the current selection of the time-frequency window width adjustment parameter is limited by the uncertainty principle, that is, the time resolution and frequency resolution of the signal cannot be optimal at the same time, and there must be a compromise

Therefore, the adjustment parameters added to the Gaussian window function can only initially determine the value range of the parameters based on a large number of experimental results, and then select them based on empirical values, which will bring certain human errors to the detection and analysis of transient power quality disturbance signals.

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