Application of Self-Adaptive Wavelet Neural Networks in Ultrasonic Detecting of Drainpipe Drainpipe

摘要：

Drainpipe ultrasonic non-destructive testing is liable to be interfered with the external environment So it is important to remove the noise signal effectively in drainpipe ultrasonic nondestructive testing. The testing system is constructed by selfadaptive wavelet neural networks which is using the wavelet and neural network algorithm. Better fitting signal is achieved by choosing Orthogonal Daubechies wavelet neuron and optimizing the scale parameter. The simulation results showed less distortion and better noise cancellation.

关键词： ultrasonic self-adaptive wavelet analysis neural networks

作者: Xi-Peng Yin Yang-Yu Fan Zhe-Min Duan Wei Cheng

作者单位: Department of Electronic Engineering Northwestern Polytechnical University,NPU Xian,Shaanxi,P.R.China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 57-59

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）