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Sensors 2013, 13(10), 12958-12974; doi:10.3390/s131012958
Article

Electrical Resistivity-Based Study of Self-Sensing Properties for Shape Memory Alloy-Actuated Artificial Muscle

,
*  and
State Key Laboratory of Mechanism System and Vibration, Institute of Robotics, Shanghai Jiao Tong University, Shanghai 200240, China
* Author to whom correspondence should be addressed.
Received: 11 July 2013 / Revised: 8 September 2013 / Accepted: 12 September 2013 / Published: 26 September 2013
(This article belongs to the Section Physical Sensors)
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Abstract

Shape memory alloy (SMA) has great potential to develop light and compact artificial muscle (AM) due to its muscle-like high power-to-weight ratio, flexibility and silent operation properties. In this paper, SMA self-sensing properties are explored and modeled in depth to imitate the integrated muscle-like functions of actuating and self-sensing for SMA-AM based on the investigation of SMA electrical resistivity (ER). Firstly, an ER transformation kinetics model is proposed based on the simulation of SMA differential scanning calorimetry (DSC) curves. Then a series of thermal-electrical-mechanical experiments are carried out to verify the validity of the ER model, whereby the SMA-AM self-sensing function is well established under different stress conditions. Finally the self-sensing capability is further demonstrated by its application to a novel SMA-AM-actuated active ankle-foot orthosis (AAFO).
Keywords: shape memory alloy; artificial muscle; self-sensing model; electrical resistivity; active ankle-foot orthosis shape memory alloy; artificial muscle; self-sensing model; electrical resistivity; active ankle-foot orthosis
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Zhang, J.-J.; Yin, Y.-H.; Zhu, J.-Y. Electrical Resistivity-Based Study of Self-Sensing Properties for Shape Memory Alloy-Actuated Artificial Muscle. Sensors 2013, 13, 12958-12974.

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