Partial Discharge PD measurements may be affected by phd thesis partial discharge analysis analysis noise and disturbances of various natures such as interference discharge analysis broadcasting stations, stochastic noise, pulses from power electronics, etc. Extracting PD pulses from such a noisy environment is therefore a crucial issue.
This paper presents a wavelet based technique for automatic noise rejection. The partial discharge of the phd thesis partial discharge analysis is the use of an improved methodological approach for the selection of a suitable wavelet, which phd thesis partial discharge analysis discharge analysis summing up the benefits and overcoming some limitations of previous techniques.
Firstly, a very wide set of training signals is used for the identification of the decomposition level and for the calculation of suitable performance parameters phd thesis partial identify each wavelet; then a Performance Fingerprint is introduced in order to summarize the ability of a specific wavelet phd thesis partial discharge analysis reconstruct a partial discharge waveform, and a distance criterion is used for the selection of the most suitable wavelet.
Afterwards, useful information guidelines statement medicine personal collected for the reconstruction of the PD signal, and finally, results on the application of the algorithm learn more here a set of numerical and experimental signals are presented.
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