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27 July 2004 OLC: a signal conditioning and calibration technique for magnetoelastic sensors
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Abstract
Magnetoelastic materials used as sensors are obtaining an increasing interest in the last few years. The magnetoelastic wave resonance frequency is the sensitive parameter generally measured to obtain key information on the magnetoelastic material; nevertheless, it was shown that also the amplitude of the magnetoelastic wave, stimulated at a frequency close to the sensor core resonance frequency (pseudo-resonance), is very sensitive to measure magnetic fields. By basing on that characteristic, both parameters, "pseudo-resonance" amplitude and resonance frequency, could be used as the "sensitive parameter" in no-contact vibration sensors or stress, flux and magnetic field sensors. In a previous paper the authors proposed a signal condition technique for magnetoelastic elements, and used it for no-contact vibration and displacement measurements. The measurements, even though had a good linearity and low distortion, comparable to that of traditional devices (LVDT or accelerometer), had a too poor repeatability, due to a time-varying behavior of the sensor magnetoelastic core. This paper proposes an On-Line self-Calibration technique for magnetoelastic sensors, OLC, that solves the repeatability problem by improving the sensor accuracy of about one order of magnitude. No external reference sensor is used, but just an easy to obtain reference stimulus. A tuning procedure is then shown, able to put the sensor into a repeatable, time-invariant status, by acting on a static polarization magnetic field. Finally, the proposed technique is applied for no-contact vibration measurements. Results are presented, comparing them with the case of no OLC applied.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Romualdo Sorrentino "OLC: a signal conditioning and calibration technique for magnetoelastic sensors", Proc. SPIE 5384, Smart Structures and Materials 2004: Smart Sensor Technology and Measurement Systems, (27 July 2004); https://doi.org/10.1117/12.539547
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