Application of self-adaptive wavelet neural networks in ultrasonic detecting of drainpipe

Xi Peng Yin, Yang Yu Fan, Zhe Min Duan, Wei Cheng

科研成果: 书/报告/会议事项章节会议稿件同行评审

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 non-destructive testing. The testing system is constructed by self-adaptive 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.

源语言英语
主期刊名Proceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010
57-59
页数3
DOI
出版状态已出版 - 2010
活动2010 IEEE International Conference on Advanced Computer Control, ICACC 2010 -
期限: 27 3月 201029 3月 2010

出版系列

姓名Proceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010
5

会议

会议2010 IEEE International Conference on Advanced Computer Control, ICACC 2010
时期27/03/1029/03/10

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