Acoustic Emission Monitoring on Crack Growth of Wind Turbine Blade Made of Fiber Glass Epoxy Plastic

Abstract:

Abstract. To extract the AE signal feature effectively, an automatically operating blind source separation method is presented. The blind deconvolution algorithm is discussed for the non-stationary AE signals to eliminate the noise through minimizing the mutual information to get the separating matrix. Finally, the experimental result is indicated that the mixing noise of the AE signals in the collecting process can be eliminated by this method, and the individual extensional and flexural wave modes can be separated, which can provides the theory analysis basis for the crack recognition of wind turbine blade.

• Periodical: Advanced Materials Research (Volumes 706-708)
• Pages: 1201-1204
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.706-708.1201
• Online since: June 2013
• Authors: Bo Zhou, Chang Zheng Chen, Yan Ling Gu, Hao Zhou
• Keywords: Acoustic Emission (AE), Blade, Blind Deconvolution Separation, Crack Monitoring, Fiber Glass

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