Study on Wavelet De-noising Methods in Welding Defects Signals

摘要

Aiming at the characteristics of friction welding pseudo bonding defects signals, such as low signal noise ratio (SNR), and cannot be detected effectively, the de-noising method based on translation invariant performs the cycle-spinning for the signal to be analyzed at first, secondly, the soft (hard) thresholding is used to de-noises the shifted signal, then one should shift the data of the de-noised signal in reverse. Do this for many times and average results so obtained. This method can get far weaker pseudo-Gibbs phenomena than thresholding based De-Noising using the traditional orthogonal wavelet transform so that it has better approximation to original signal. In this paper it is used to de-noise the tested defects signal of friction welding. Simulated experiment shows that this method greatly improves the de-noising effect.