Title : 
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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2011 International Conference on
         
        
            Conference_Location : 
Zhejiang
         
        
            Print_ISBN : 
978-1-4577-0676-9
         
        
        
            DOI : 
10.1109/IHMSC.2011.46