Power transmission line fault reason identification method based on high and low frequency wavelet feature association

Abstract

The invention discloses a power transmission line fault season identification method based on high and low frequency wavelet feature association, which comprises the steps of extracting fault phase current samples of N failure types, and building a sample database; performing high frequency and low frequency data sampling on a fault type T from the sample database, and respectively performing wavelet decomposition; performing feature extraction on a high frequency data wavelet coefficient and a low frequency data wavelet coefficient; S4, building an association relationship model of the fault type T; determining the association relationship model of the N fault types; S6, performing wavelet decomposition on sample data whose fault reason is to be tested, and extracting a feature vector; substituting the feature vector of the sample whose fault reason is to be tested to the association relationship models of the N fault types, and judging the fault type of the sample data whose fault reason is to be tested. According to the invention, fault phase current is analyzed and processed through combining a wavelet transform theory and an information entropy, thereby not only being capable of effectively analyzing suddenly changed signals, but also being capable of achieving a purpose of information fusion, and improving the identification accuracy.

Description

technical field [0001] The invention relates to the technical field of transmission line fault diagnosis, in particular to a transmission line fault cause identification method based on high and low frequency wavelet feature correlation. Background technique [0002] The high-voltage transmission line is the place where the most faults occur in the transmission network, and its faults have very serious harm and impact on the stable operation of the power system, national economic construction and people's daily life. After a fault, rapid and accurate fault cause analysis plays an important role in the inspection and maintenance of the staff and the rapid restoration of power supply to the grid. The main causes of transmission line failures are lightning strikes, pollution flashovers, bird flashes, mountain fires, foreign object short circuits, and external force contact. [0003] Based on the analysis of the above-mentioned various fault mechanisms, the corresponding featur...

AI Technical Summary

Problems solved by technology

However, most of the actual on-site wave recording data is the wave recording data with a sampling frequency less than 10K, which contains relatively little frequency and time domain information, which brings great difficulties to the identification of the cause of the fault.

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