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Classical and modern power spectrum estimation for tune measurement in CSNS RCS 被引量:2

Classical and modern power spectrum estimation for tune measurement in CSNS RCS
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摘要 Precise measurement of betatron tune is required for good operating condition of CSNS RCS.The fractional part of betatron tune is important and it can be measured by analyzing the signals of beam position from the appointed BPM.Usually these signals are contaminated during the acquisition process,therefore several power spectrum methods are used to improve the frequency resolution.In this article classical and modern power spectrum methods are used.In order to compare their performance,the results of simulation data and IQT data from J-PARC RCS are discussed.It is shown that modern power spectrum estimation has better performance than the classical ones,though the calculation is more complex. Precise measurement of betatron tune is required for good operating condition of CSNS RCS. The fractional part of betatron tune is important and it can be measured by analyzing the signals of beam position from the appointed BPM. Usually these signals are contaminated during the acquisition process, therefore several power spectrum methods are used to improve the frequency resolution. In this article classical and modern power spectrum methods are used. In order to compare their performance, the results of simulation data and IQT data from J-PARC RCS are discussed, It is shown that modern power spectrum estimation has better performance than the classical ones, though the calculation is more complex.
出处 《Chinese Physics C》 SCIE CAS CSCD 2013年第11期79-83,共5页 中国物理C(英文版)
关键词 RCS测量 功率谱估计 古典 感应加速器 功率谱方法 信号采集 频率分辨率 精确测量 tune, signal processing, power spectrum estimation, frequency resolution, IQT data
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  • 1WEI J, FANG S X, FENG J et al. China Spallation Neutron Sources: Design. In: Proceedings APAC 2007. Indore: Dr. Sahni V C, 2007. 310-314.
  • 2NIRMAL SINGH, MAMTA KATIYAR. International Jour?nal of Electronics Communication and Computer Engineering, 2012, 3: 15-17.
  • 3Welch P D. IEEE Trans. Audio Electroacoust, 1967, AU-I5: 70-73.
  • 4Kay S M. Modern Spectral Estimation. Englewood Cliffs, NJ: Prentice Hall, 1988.
  • 5LI Li, HE Hong. Research on Power Spectrum Estimation Based on Periodogram and Burg Algorithm. In: International Conference on Computer Application and System Modeling 2010. Taiyuan: ICCASM201O.V3695-698.
  • 6WANG Guang- Yan, WANG Xia, ZHAO Xiao-Qun. Speech En?hancement Based on a Combined Spectral Subtraction with Spectral Estimation in Various Noise Environment. In: Inter- national Conference on Audio, Language and Image Processing 2008. Shanghai: ICALIP2008. 1424-1429.
  • 7John Musson, LI Jiang. A Comparative Survey of PSD Esti?mation Method for EEG Signal Analysis. http://www.vmase. odu .ed u/ downloads / Capstone. Papers /Medical/M usson. pdf.
  • 8Proakis J G, Manolakis D G. Digital Signal Processing: Prin?ciples, Algorithms, and Applications. Englewood Cliffs, NJ: Prentice Hall, 1996.
  • 9Zbigniew Leonowicz, Tadeusz Lobos, Jacek Rezmer. IEEE Transactions on Industrial Electronics, 2003, 50(3): 514-519.
  • 10Petre Stoica, LI Jian, HE Hao. Spectral Analysis of Nonuni?formly Sampled Data: A New Approach Versus the Pe?riodogram. IEEE Transactions on Signal Processing, 2009, 57(3): 843-858.

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