@inproceedings{d33cd44cf2f141a8b35a9bc5e6732ba1,
title = "The application of self-adaptive wavelet neural network in multi-layered structure ultrasonic testing of the solid rocket-motor",
abstract = "It is important to remove the noise signal effectively in non-destructive ultrasonic testing. Use the wavelet and neural network algorithm in multi-layered structure ultrasonic testing system of the solid rocket-motor, and construct self-adaptive wavelet neural network in the ultrasonic testing in order to restrain the noise. Better fitting signal is achieved by choosing Orthogonal Daubechies wavelet group and optimize the scale parameter by a searching algorithm. The simulation result shows that the wavelet neural network can make the testing system less distortion and better noise cancellation, and the method can be widely applied to ultrasonic detecting.",
keywords = "Neural network, Self-adaptive, Ultrasonic, Wavelet analysis",
author = "Yin, {Xi Peng} and You Li and Wei Cheng and Chang Chen",
year = "2013",
doi = "10.4028/www.scientific.net/AMM.421.474",
language = "英语",
isbn = "9783037858783",
series = "Applied Mechanics and Materials",
pages = "474--478",
booktitle = "Information Technology for Manufacturing Systems IV",
note = "4th International Conference on Information Technology for Manufacturing Systems, ITMS 2013 ; Conference date: 28-08-2013 Through 29-08-2013",
}