Application of Particle Swarm Optimization Algorithm to Denoising Vibration Signal of Gearbox

  • ZHANG Pengtao ,
  • LIU Jinhao
  • 1. College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China;
    2. Engineering College, Beijing Forestry University, Beijing 100083, China

Received date: 2014-01-22

  Revised date: 2014-03-24

  Online published: 2014-05-19


Taking the gearbox in wind turbine as an example, this paper introduces a method about denoising the vibration signal of gearbox based on the vibration spectrum analysis and particle swarm optimization algorithm. The particle swarm optimization algorithm can reduce the search space by using one dimension search, and improve the optimization result by simultaneously optimizing the design parameters of Chebyshev band pass filter and Morlet wavelet filter, eventually filtering out the fault vibration signal of the gearbox. Experimental results show that this method can effectively eliminate the external noise in the vibration signal, and that the hybrid algorithm can effectively reduce the search range of particle swarm optimization and improve the optimization result for the relevant parameter optimization of Chebyshev band-pass filter and Morlet wavelet filter. It is applicable to the real-time gearbox fault diagnosis research. Therefore, it has certain value for theoretical research and practical applications. This hybrid algorithm has good optimized performance and the optimization process is fast. The fault features are obvious in the denoised signal, and can be applied to the real-time fault diagnosis of gearbox in the future research.

Cite this article

ZHANG Pengtao , LIU Jinhao . Application of Particle Swarm Optimization Algorithm to Denoising Vibration Signal of Gearbox[J]. Science & Technology Review, 2014 , 32(13) : 28 -32 . DOI: 10.3981/j.issn.1000-7857.2014.13.004


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