Abstract
This paper presents an induced voltage linear extraction method for disturbing force self-sensing in the application of giant magnetostrictive actuators (GMAs). In this method, a Kelvin bridge combined with an active device is constructed instead of a conventional Wheatstone bridge for extraction of the induced voltage, and an additional GMA is adopted as a reference actuator in the self-sensing circuit in order to balance the circuit bridge. The linear fitting of the measurement data is done according to the linear relationship between the disturbing forces and the integral of the induced voltage. The experimental results confirm the good performance of the proposed method, and the self-sensitivity of the disturbing forces is better than 2.0 (mV·s)/N.
Highlights
Giant magnetostrictive actuators (GMAs) are a new type of micro-displacement actuator that exhibit good driving characteristics under the action of a constant force [1,2,3]
We proposed a linear extraction method for induced voltage based on the Kelvin bridge
Dynamic equivalent circuit model of GMA was analyzed with the concept of an active Kelvin bridge
Summary
Giant magnetostrictive actuators (GMAs) are a new type of micro-displacement actuator that exhibit good driving characteristics under the action of a constant force [1,2,3]. Nonlinear displacement output appears owing to the coupling between the positive magnetostrictive effect and the inverse magnetostrictive effect Another drawback in the realization of positioning precision is the nonlinear method for the extraction of the induced voltage. GMA self-sensing of external disturbing forces is achieved by the indirect measurement of the induced voltage signal. The GMA self-sensing signal detection method based on a Wheatstone bridge was proposed. In 2004, Kuhnen K. et al compared the two kinds of self-sensing methods proposed by the LPA, and found that the coil inductance indirect measurement method is affected by the irreversible current and the method using hall sensors to detect the magnetic field has good linearity [18]. The positioning performance was improved when the friction influence on load was offset by applying the method
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