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

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.