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Influence of wavelet level, used in denoising AE signals process, on signal spectrum parameters

Dobrzycki A., Opydo W.

Poznan University of Technology Academic Journals. Electrical Engineering

2009

No 60

81-85

The paper presents the results of investigation of influence wavelet function parameters on chosen signal spectrum parameters. Wavelets were used in denoising AE signals connected with electrical treeing process. Analyzed spectrum parameters were: maximum, average, median and minimum amplitude. Influence of wavelet level to compute time was also analyzed.

Damage detection and estimation using wavelet transform

Ziopaja K., Pozorski Z.

Foundations of Civil and Environmental Engineering

2006

No. 7

413-421

In the present paper mechanically loaded 1-D structures and thermally loaded 2-D structures are considered. In case of 1-D members, response signals in the form of displacements are processed, whereas in 2-D structures temperature fields are used. Employing the discrete wavelet transform of the response signals the damage zones are discovered and localized. In case of 1-D structures the Lipschitz exponent was estimated using the local maxima of the wavelet transform modulus as an intensity factor, which served to assess the magnitude of damage.

The wavelet transform - a new method to analyse the Barkhausen effect. IBN - identified Barkhausen noise.

Magalas L.B., Malinowski T.

Inżynieria Materiałowa

1998

R. XIX, nr 3

364-367

A new approach to the Barkhausen noise (BN) based on wavelet analysis is presented. The BN level is usually expressed with the magnetoelastic parameter MP - relative number, which is proportional to the RMS (Root Mean Square) level of the BN. This approach is used in this paper in order to establish the relationship between the BN and the level of internal stresses. The application of the wavelet transform to studies of the Barkhausen effect is a new area, which we started in 1995. To our knowledge, we are the only laboratory in Poland that uses this approach. We expect, however, that the wavelet transform will soon become a standard tool in analysis of the Barkhausen effect.