Advertisement

The Design of Power Quality Detecting System Based on ADSP-BF606

  • Yunhua Zhang
  • Fenghou PanEmail author
  • Qiang Gao
  • Feng Yuan
  • Jiayu Pan
  • Zailin Li
  • Jicheng Dai
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 921)

Abstract

The low cost and the multi-function have been the main contradiction of power quality detecting devices. For it, this paper designs a power quality detecting system based on the latest ADI’s ADSP-BF606 dual-core processor. With the high-speed AD7606 chip, the system achieves real-time data acquisition, processing, and analysis. The hardware design makes the system highly integrated, lower cost and easy to be integrated into the enterprise information management system. The fast flourier transformation with window and interpolation is adapted to detect harmonic, and S-Transform is used to detect and locate interferences automatically and quickly, wavelet package transform and binary tree support vector machine are also used to make interference classifications. Experiment results show that this design meets the requirements and different algorithms make the system more automatic and intelligent. The system with low cost and the multi-function is better than others.

Keywords

Power quality detecting system Dual-core processor Data acquisition processing analysis 

References

  1. 1.
    Xiao, X.: Power quality analysis and control. China Electric Power Press Beijing 44(2), 45–47 (2004). (in Chinese)Google Scholar
  2. 2.
    Zhang, G., Ma, X., Lei, Y.: The design of the power quality monitoring devices based on TMS320C6713. Electron. Measur. Technol. 1(33), 83–86 (2010). (in Chinese)Google Scholar
  3. 3.
    Haydn, G.T.: Applications of the windowed FFT to electric power quality assessment. IEEE Trans. Power Deliv. 14(14), 6–11 (2004)MathSciNetGoogle Scholar
  4. 4.
    Zhu, X., Su, H.: Power quality disturbances analysis based on the S-transform. Yunnan Electric Power 3(7), 7–15 (2009). (in Chinese)Google Scholar
  5. 5.
    Ma, Z., Li, P., Yang, Y.: Power quality detecting based on wavelet multi-resolution method. J. North China Electric Power Univ. 3(1), 3–6 (2003). (in Chinese)Google Scholar
  6. 6.
    Qiao, Z., Sun, W.: A multi-class classifier based on the SVM decision tree. Comput. Appl. Softw. 11, 227–230 (2009)Google Scholar
  7. 7.
    Sun, F., Zhang, S., Wang, T.: Debugging and operation technology for the intelligent substation. China Electric Power Press, 27(10) (2014). (in Chinese)Google Scholar
  8. 8.
    Wang, F., Pan, S.: Debugging technology of secondary system for intelligent substation. China Electric Power Press, 29(15) (2013). (in Chinese)Google Scholar
  9. 9.
    Harris, F.J.: On the use of windows for harmonic analysis with the discrete Fourier transform. Proc. IEEE 66(1), 51–83 (1978)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yunhua Zhang
    • 1
  • Fenghou Pan
    • 1
    Email author
  • Qiang Gao
    • 1
    • 2
  • Feng Yuan
    • 1
  • Jiayu Pan
    • 1
  • Zailin Li
    • 1
  • Jicheng Dai
    • 1
  1. 1.State Grid Liaoning Electric Power Research InstituteShenyangChina
  2. 2.Shanghai Jiao Tong UniversityShanghaiChina

Personalised recommendations