Detection and classification of material attributes-a practical application of wavelet analysis

Author

Maass, Peter ; Teschke, Gerd ; Willmann, Werner ; Wollmann, Günter

Author_Institution

Zentrum fur Technomath., Bremen Univ., Germany

Volume

48

Issue

8

fYear

2000

fDate

8/1/2000 12:00:00 AM

Firstpage

2432

Lastpage

2438

Abstract

We describe a method for classifying material properties from measurements of the Barkhausen effect, which originates from a fast magnetization of ferromagnetic materials using alternating currents. We use wavelet analysis to develop a tool box for evaluating Barkhausen measurements. The described wavelet techniques allow detection of extremely weak signals in the Barkhausen noise voltage. By using a statistical classification rule, we show that the detected structures are directly related to material properties

Keywords

Barkhausen effect; ferromagnetic materials; magnetic noise; noise measurement; signal classification; signal detection; statistical analysis; wavelet transforms; Barkhausen effect measurements; Barkhausen noise voltage; alternating currents; fast magnetization; ferromagnetic materials; material attributes classification; material attributes detection; material properties; statistical classification rule; tool box; wavelet analysis; weak signals detection; Frequency; Magnetic analysis; Magnetic domains; Magnetic materials; Magnetization; Material properties; Noise measurement; Voltage; Wavelet analysis; Wires;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.852022

Filename

852022