Analysing MBN signals of different materials by time-frequency methods

Linilson Padovese (1) , Nadine Martin (2) , Julien Huillery (2)

1 Department of Mechanical Engineering
2 GIPSA-SA-IGA - GIPSA - Signal et Automatique pour le Diagnostic et la Surveillance

Due to the fact that Magnetic Barkhausen Noise (MBN) carries out information about the microstructure and stress behavior of ferromagnetic steels, it has been using as a basis for effective Non Destructive Testing (NDT) methods, opening new areas in NDT industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as, amplitude maxima, signal root mean square, and so on. This paper presents a new approach based on the MBN time-frequency analysis. The experimental case that illustrates this approach regards the use of MBN signals to characterize different types of steels. It is shown that, due to non-stationary characteristics of the MBN, time-frequency representations can provide a rich and new panorama of these signals. Extraction techniques of some time-frequency parameters are used to allow a diagnostic process. A comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the proposed method.

Mots clés: Magnetic Barkhausen Noise; Bloch wall; non destructive testing; time-frequency; diagnostic; gliding Capon estimator; signature; material

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Linilson Padovese, Nadine Martin, Julien Huillery. Analysing MBN signals of different materials by time-frequency methods. CM 2008 - MFPT 2008 - 5th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Jul 2008, Édimbourg, United Kingdom. ⟨hal-00285873⟩