Study on Transient Signal Detection in Power System Based on Wavelet Transform
Diao Yanhua, Chunming Li
Abstract
Diao Yanhua, Chunming Li
Abstract
The application of wavelet analysis in transient signal detection of power systems is growing rapidly. In this paper, according to the theory of detecting signals with wavelet transformation, a new transient signal feature detection scheme is introduced, It is based on wavelet transform, particularly the multiresolution analysis technique. This work focuses on how to use the wavelet transform to locate signal abrupt points, at the same time, we also describes the significant properties of wavelet base and how to choice a appropriate wavelet. The effectiveness of the proposed scheme was verified in the experiment. The simulation result shows that this method has the ability of simple algorithm, high location accurance, can effectively improve the sensitivity and selectivity. Furthermore the prospect of wavelet analysis in power system, especially in fault diagnosis is estimated.
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The application of wavelet analysis in transient signal detection of power systems is growing rapidly. In this paper, according to the theory of detecting signals with wavelet transformation, a new transient signal feature detection scheme is introduced, It is based on wavelet transform, particularly the multiresolution analysis technique. This work focuses on how to use the wavelet transform to locate signal abrupt points, at the same time, we also describes the significant properties of wavelet base and how to choice a appropriate wavelet. The effectiveness of the proposed scheme was verified in the experiment. The simulation result shows that this method has the ability of simple algorithm, high location accurance, can effectively improve the sensitivity and selectivity. Furthermore the prospect of wavelet analysis in power system, especially in fault diagnosis is estimated.
Key concepts: Wavelet, Wavelet transform, Lifting scheme, Second-generation wavelet transform, Wavelet packet decomposition, Stationary wavelet transform, Discrete wavelet transform, Computer science