Recommended Wavelet Based Practices for the Estimation of Electromagnetic Noise in Different Operational Contexts
Ileana-Diana Nicolae, Dusan Kostic, Petre-Marian Nicolae, Marian-Ştefan Nicolae · 2022 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI) · 2022
Signals acquired from an industrial environment with many sources of electromagnetic interferences may be polluted by white noise. The decompositions based on the Stationary and Discrete Wavelet Transformations, respectively the Wavelet Packet Decomposition can be used to estimate the power of noise affecting a certain waveform. Original linear combinations of powers of vectors of details hosted by the nodes of the unbalanced trees generated by the Stationary and Discrete Wavelet Decompositions were conceived in order to evaluate the power of noise which is used afterward by thrashing trees. Tests were made on currents and voltages acquired in different operational contexts. “Smoothed” versions of denoised signals, obtained in an original way with Wavelet Packet Trees were used as reference. The paper is meant to provide a usefull tool for deciding which is the best thrashing practice considering criteria like: minimum relative percentage difference (estimated vs reference) between the powers of noise, maximum deviation, mean square error and runtime. Two wavelet mothers (symlet with filter of 8 components and Daubechies with filter of 28 components) were studied for signals with 512 components per period and trees with 7 levels.