@ARTICLE{Wang_Rongkun_Tracking_2020,
 author={Wang, Rongkun and Sun, Sigun and Hu, Bingtao},
 volume={vol. 27},
 number={No 2},
 journal={Metrology and Measurement Systems},
 pages={339-353},
 howpublished={online},
 year={2020},
 publisher={Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation},
 abstract={Assessment of the state of a pulse power supply requires effective and accurate methods to measure and reconstruct the tracking error. This paper proposes a tracking error measurement method for a digital pulse power supply. A de-noising algorithm based on Empirical Mode Decomposition (EMD) is used to analyse the energy of each Intrinsic Mode Function (IMF) component, identify the turning point of energy, and reconstruct the signal to obtain the accurate tracking error. The effectiveness of this EMD method is demonstrated by simulation and actual measurement. Simulation was used to compare the performance of time domain filtering, wavelet threshold de-noising, and the EMD de-noising algorithm. In practical use, the feedback of current on the prototype of the power supply is sampled and analysed as experimental data.},
 type={Article},
 title={Tracking error analysis method of digital pulse power supply for heavy ion accelerator based on emd reconstruction},
 URL={http://ochroma.man.poznan.pl/Content/116017/PDF/art10.pdf},
 doi={10.24425/mms.2020.132779},
 keywords={pulse power supply, tracking error, EMD, signal reconstruction},
}