Title :
Application of Signal Detection for Pipeline Flaw Based on Wavelet Neural Network
Author :
Zhou, Runjing ; Zhang, Fei
Author_Institution :
Inner Mongolia Univ., Hohhot
Abstract :
Aiming at denoising to detection signal of the flaw in the long transporting pipe, the way of denoising based on wavelet neural network is present, and signal processing of ultrasonic detection application in long pipeline is described. Making use of self-learning characteristic of wavelet neural network, this way reduces wave loss. This method has the good effect and may acquire exact location and amplitude of the flaw. It is great significance for signal processing of ultrasonic detection.
Keywords :
neural nets; pipelines; signal denoising; signal detection; wavelet transforms; pipeline flaw; signal detection; ultrasonic detection; wavelet neural network; Integral equations; Neural networks; Neurons; Noise reduction; Petroleum; Pipelines; Signal analysis; Signal detection; Signal processing; Wavelet analysis;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.263