Analysis of Sparse Fourier Transform for Vibration Signal of Wind Turbine Gearbox

doi:10.11930/j.issn.1004-9649.2016.08.069.05

Abstract

Abstract: The on-line spectrum analysis for vibration signal of wind turbine gearbox demands fast algorithms. In order to improve the speed of the algorithm, the spectrum analysis with Sparse Fast Fourier Transform (SFFT) algorithm is proposed in this paper. First, the SFFT algorithm is used to leverage the window function to filter vibration signal. Then, after the Fourier coefficients being hashed, the k largest (in magnitude) coefficients of the Fourier Transform of vibration signal can be estimated by locating and estimating methods. The SFFT algorithm has a simple structure and a sub-linear runtime in the signal size n. It has been verified through analyzing the vibration signal of wind turbine gearbox that the SFFT algorithm has a faster performance than FFT algorithm in on-line spectrum analysis.

Key words: wind turbine, gearbox, vibration signal, spectrum analysis, Sparse Fast Fourier Transform

CLC Number:

TM614

ZHAO Hongshan, GAO Duo, ZHANG Jianping. Analysis of Sparse Fourier Transform for Vibration Signal of Wind Turbine Gearbox[J]. Electric Power, 2016, 49(8): 69-73.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.2016.08.069.05

https://www.electricpower.com.cn/EN/Y2016/V49/I8/69

References

[1] 张路朋，赵洪山．基于时间延迟的风机齿轮箱状态优化维修[J]．中国电力，2014，47（11）：108-111．
ZHANG Lupeng, ZHAO Hongshan． Optimized condition based maintenance for gearbox of wind turbine based on time-delay[J]．Electric Power, 2014, 47(11): 108-111．
[2] MILOVANCEVIC M, ANDELKOVIC B． Modern techniques of wind turbine condition monitoring[J]． Journal of Applied Engineering Science, 2010, 8(1): 33-38．
[3] 崔翔．信号分析与处理[M]．北京：科学出版社，2005：29-30．
[4] 黄沈阳．新型环境保护分析系统——傅立叶变换红外分析系统[J]．中国电力，2004，36（11）：90－92．
HUANG Shenyang． A new type gas analysis system in environment protection: Fourier transform infrared analysis system [J]． Electric Power, 2004, 36(11): 90-92．
[5] VAN NEE D J R, COENEN A． New fast GPS code-acquisition technique using FFT[J]． Electronics Letters, 1991, 27(2): 158-160．
[6] 任重，董明，吴立远．采用傅立叶变换分析冲击GIS局部放电信号[J]．中国电力，2013，46（4）：48－53．
REN Zhong, DONG Ming, WU Liyuan． Analysis of partial discharge in GIS under impulse voltage by using quadratic short-time fourier transform [J]． Electric Power, 2013, 46(4): 48-53．
[7] REDDY B S, CHATTERJI B N． An FFT-based technique for translation, rotation, and scale-invariant image registration[J]．IEEE Transactions on Image Processing, 1996, 5(8): 1266-1271．
[8] MURSHUDOV G N, VAGIN A A, LEBEDEV A, et al． Efficient anisotropic refinement of macromolecular structures using FFT[J]．Acta Crystallographica Section D: Biological Crystallography,1999, 55(1): 247-255．
[9] HASSANIEH H, INDYK P, KATABI D, et al． Simple and practical algorithm for sparse Fourier transform[C]//Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms． SIAM, 2012: 1183-1194．
[10] HASSANIEH H, INDYK P, KATABI D, et al． Nearly optimal sparse fourier transform[C]//Proceedings of the forty-fourth annual ACM symposium on Theory of computing, ACM, 2012: 563-578．
[11] 邓亚玲，胡元义，王新房．基于 Hash 函数的用户口令保护方法的研究[J]．计算机工程，2002，28（8）：195-197．
DENG Yaling, HU Yuanyi, WANG Xinfang． Research on user password protection method based on hash function [J]． Computer Engineering, 2002, 28(8): 195-197．
[12] SMITH J O． Mathematics of the discrete fourier transform (DFT):With music and audio applications [M]． Julius Smith, 2007．
[13] GILBERT A C, MUTHUKRISHNAN S, STRAUSS M. Improved time bounds for near-optimal sparse Fourier representations[C]//Optics & Photonics 2005． International Society for Optics and Photonics,2005: 59141A-59141A-15．
[14] HARRIS F J． On the use of windows for harmonic analysis with the discrete Fourier transform[J]． Proceedings of the IEEE, 1978, 66(1): 51-83．
[15] SCHUMACHER J, Puschel M． High-performance sparse fast Fourier transforms[C]//Signal Processing Systems(SiPS), 2014 IEEE Workshop on． IEEE, 2014: 1-6．