Open AccessOnline current signal de‐noising of magnetic bearing switching power amplifier based on lifting wavelet transform
Author(s) -
Zhang Huijuan,
Fang Jiancheng,
Liu Hu
Publication year - 2016
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
ISSN - 1751-8679
DOI - 10.1049/iet-epa.2015.0457
Subject(s) - wavelet , wavelet transform , bearing (navigation) , signal (programming language) , amplifier , electronic engineering , computer science , wavelet packet decomposition , power (physics) , electrical engineering , lifting scheme , signal processing , engineering , acoustics , physics , artificial intelligence , cmos , digital signal processing , quantum mechanics , programming language
Switching power amplifier is an essential component for magnetic bearing system. However, the current ripple resulted from the conduction and shutoff operation of power switch component inevitably affects the performance of active magnetic bearing. To reduce the current ripple of switching power amplifier, the characteristics of current ripple are first analysed. In response to the spectrum character of current ripple, an online lifting wavelet transform de‐noising algorithm, unlike the conventional power filter circuit, is proposed in this study. Moreover, the sliding data window and an improved threshold function are introduced to realise the feasibility of online processing and to improve the de‐noising performance, respectively. Finally, plentiful comparative experiments, taking the magnetically suspended flywheel as subject, are implemented. The results illustrate that the proposed algorithm could dramatically reduce the current ripple and that the rotor displacement jitter and the vibration force are suppressed accordingly.