Tracking error analysis method of digital pulse power supply for heavy ion accelerator based on emd reconstruction

• Autorzy: Wang Rongkun , Sun Sigun , Hu Bingtao

Identyfikatory

DOI

10.24425/mms.2020.132779

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

pulse power supply; tracking error; EMD; signal reconstruction

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2020
• Tom: Vol. 27, nr 2
• Strony: 339--353
• Opis fizyczny: Bibliogr. 34 poz., rys., tab., wykr., wzory

Twórcy

autor

Wang Rongkun

• Huaqiao University, School of Information Science and Engineering, Xiamen 361021, China

autor

Sun Sigun

• Huaqiao University, School of Information Science and Engineering, Xiamen 361021, China

autor

Hu Bingtao

• Huaqiao University, School of Information Science and Engineering, Xiamen 361021, China

Bibliografia

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Uwagi

EN

1. This research was supported by Institute of Modern Physics, Chinese Academy of Sciences. The authors thank the Institute for providing the power supply prototype and experimental environments. This work is supported by the National Natural Science Foundation of China [grant number 51707068], the Natural Science Foundation of Fujian Province [grant number 2017J01097].

PL

2. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).