Lamb wave signal denoising method based on John Saris model and fractional differentiation

Abstract

The invention provides a Lamb wave signal denoising method based on a John Saris model and fractional differentiation. The method overcomes the defects in the prior art, and the signal to noise ratio of denoised signals is increased. The method includes the steps that various-order fractional differentiation is conducted on a Lamb wave signal amplitude spectrum containing noise, John Saris distribution is used as a model of the amplitude spectrum to be processed, a cubic relation between a fractional differentiation maximum value and a zero crossing point of the John Saris model amplitude spectrum and a differential order is provided, a calculation formula of characteristic parameters of the amplitude spectrum is built to extract characteristic parameters and rebuild an amplitude spectrum of original signals, and then denoised Lamb wave signals are reconstructed by the combination of a phase spectrum.

Description

Technical field: [0001] The invention relates to the technical field of ultrasonic Lamb wave signal processing in nondestructive testing, in particular to a Lamb wave signal denoising method based on the Celes model and fractional differential. Background technique: [0002] In the ultrasonic Lamb wave detection, because the Lamb wave excitation and inspection methods are flexible, and can effectively interact with the plate defects, and carry a large amount of information, it can be used as an effective means of plate defect detection, especially in large areas. It is more widely used in the non-destructive testing of plate structures. Ultrasonic Lamb wave signal is a typical non-stationary signal. In actual detection, because the signal is subject to different degrees of noise interference, the received signal components become very complex, which brings errors to the later processing and directly affects the reliability of detection. Therefore, it is necessary to denoise...

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Problems solved by technology

Li Gang et al. used the EMD method to denoise the ultrasonic Lamb wave signal. Although the EMD method does not need to be based on a specific function and can adaptively extract data according to the signal characteristics, the denoising effect is not thorough and a lot of noise is retained. The characteristics of the signal cannot reflect the original signal well, and the denoising effect is not ideal (LiG, ShiLH, WangXW. EMD denosing method and its application in Lambwave detection, Acta Metrologica Sinica, 2006, 27: 149-152)

Due to the advantages of wavelet transform in denoising, it has been widely used in the field of non-destructive testing. Siqueir et al. used discrete wavelet transform to process the ultrasonic Lamb wave measured signal, and decomposed the signal smaller than a given threshold value through the hard threshold method. The coefficient is set to 0. However, although this method removes the noise, the denoising effect is not ideal, and the signal still contains a lot of noise, so the reconstructed signal cannot accurately reflect the characteristics of the signal (SiqueiraMHS, GattsCEN, SilvaRRetal.Theuseofultrasonicguidedwavesandwaveletsanalysisinpipeinspection, Ultrasonics, 2003, 41:785-798)

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