Title :
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
fDate :
8/1/2000 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
