A new adaptive automated feedback system for Barkhausen signal measurement

Governing conditions of repeatable Barkhausen noise response

“…However, this leads to its conformity with the RMS value of BN (see Fig. 3(b)) [22]. The main problem with BN jump evaluation is the separation of background noise, as shown in Fig.…”

“…The skin effect led to the exponentially decaying signal of the sample coil spectra correlating with the magnetic induction rate [1,4,17,25]. The dB=dt proportionality, however, should be additionally checked by measurement with a controlled induction rate [2,5,22]. The exponential fitting and low-pass filtering showed that the majority of detectable BN for the considered ferromagnetic materials is within the 30 kHz upper limit (see Figs.…”

“…The difference between the RMS value and spectral energy in the 2-70 kHz range demonstrates the level of remaining noise outside this frequency region. According to Parseval's theorem, the total spectral energy in the whole range up to the Nyquist frequency (power spectrum) equals the RMS value of the signal, which is always fulfilled experimentally [12,22].…”

“…However, the AC BN measurement is unstable due to variations of the sample magnetic properties and of the yoke lift-off [5,9]. The appropriate solution to this problem is control of the magnetization conditions by a feedback system, keeping the field/flux waveform identical to a prescribed standard [2,22,26].…”

Correlation Between AC Core Loss and Surface Magnetic Barkhausen Noise in Electric Motor Steel

“…An in-house designed and built flux controller combines an analog circuit with a digital algorithm for rapid surface measurements with minimum error in the control loop [25]. Control of flux reduces the likelihood of potential artifact effects such as those introduced by air gaps, and increases the reproducibility of measurement results [25][26][27].…”