Acoustic Emission Testing Research of Composites Bearing Based on Neural Network

Author

Jianing, Wang ; Zhenkai, Wan

Author_Institution

Comput. Technol. & Software Dept., Tianjin Polytech. Univ., Tianjin, China

Volume

1

fYear

2011

Firstpage

165

Lastpage

168

Abstract

This paper will apply the Acoustic Emission(AE) technique principle to detect the AE signals of the three-dimensional braided composites under tension and compression test mode and apply wavelet analysis to reduce the AE signal noise. The filtered AE waveform or waveform parameters will be treated as a sample to be input to Back Propagation(BP) neural network, after the training, BP neural network will automatically identify the load bearing of three-dimensional braided composite materials and its corresponding damage model.

Keywords

acoustic emission testing; backpropagation; compressive testing; machine bearings; mechanical engineering computing; neural nets; signal detection; structural engineering; tensile testing; wavelet transforms; woven composites; AE signal noise; AE technique principle; AE waveform; BP neural network; BackPropagation; acoustic emission testing; composites bearing; compression test mode; damage model; load bearing; tension test mode; three-dimensional braided composite; wavelet analysis; Acoustic emission; Composite materials; Load modeling; Optical fiber networks; Time frequency analysis; Wavelet analysis; Wavelet transforms; AE; BP neural network; damage model; load bearing; three-dimensional braided composites; wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2011 International Conference on

Conference_Location

Zhejiang

Print_ISBN

978-1-4577-0676-9

Type

conf

DOI

10.1109/IHMSC.2011.46

Filename

6038172