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EN
The aim of the paper was to study the features of measurement of the magnetic Barkhausen noise by the new two-stage method in the high excitation frequency region (power line frequency). The magnetic Barkhausen noise was investigated on grain oriented Fe-3%Si steel subjected to different heat treatment. By application of an air coil on the output of the power amplifier we were able to linearize the excitation field. At the same time, the air coil suppressed the unwanted noise from the output of the power amplifier. We have found that the two-stage method is able to reveal a peak of the power spectrum even if it is located at low frequency, in contrast to the classical one-stage method. Further, we successfully applied a model of the power spectrum to the real magnetic Barkhausen noise obtained from the two-stage measurement.
EN
The Barkhausen noise was measured in plastically deformed low-carbon steel at various frequencies of the magnetizing field. Strip samples magnetized by a yoke were used for investigation. The measured amplitude distributions and power spectra are compared with the results of the Alessandro, Beatrice, Bertotti, Montorsi model of the Barkhausen noise. The measurement results at the triangular magnetizing current and the triangular magnetic field in the sample were compared and the differences will be discussed.
EN
A new method of the Barkhausen noise measurement and optimization of the measured data processing with respect to non-destructive evaluation of ferromagnetic materials is proposed. The measuring method is based on well-known method of magnetic adaptive testing where a complex set of minor hysteresis loops is measured. Collecting the sets of obtained Barkhausen noise envelopes into suitable designed matrices and optimizing the data processing with respect to the maximum sensitivity to the evaluated variable were developed. The method is illustrated on the evaluation of plastic deformation of a steel sample. It is shown that the proposed measuring method and measured data processing bring an improvement of the sensitivity to the evaluated variable when comparing with measuring the traditional Barkhausen noise parameter (root mean square).
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