Journal article
A resistance-only approach for shape memory alloy wire adaptive monitoring with auxiliary winding temperature-sensing wire
- Abstract:
- Shape memory alloy (SMA) wires offer unique properties ideal for diverse engineering applications such as robotics and aerospace. However, precise monitoring of SMA wires remains challenging in dynamic operational environments. This paper introduces a novel adaptive monitoring approach using dual electrical resistance measurements: the intrinsic resistance of the SMA wire itself and the resistance of an auxiliary temperature-sensing wire wound around the SMA wire. A simple example of a theoretical prediction model for stress and strain is studied, in which strain predictions are based on the SMA wire’s temperature and electrical resistance, and then the temperature and the predicted strain are combined to assess the stress of the SMA wire. Experimental validation under dynamic loading and variable environmental conditions confirms the approach’s feasibility and repeatability. The results demonstrate that the proposed approach can effectively monitor stress and strain in the SMA wire by measuring only two resistances, surpassing traditional methods in adaptability and repeatability. This advantage has the potential to enhance the performance and functionality of SMA-based devices. Furthermore, this approach is universal, allowing researchers to select alternative theoretical prediction models that best meet their requirements without being restricted to the one in this paper.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 4.2MB, Terms of use)
-
- Publisher copy:
- 10.1016/j.ymssp.2024.112280
Authors
+ National Natural Science Foundation of China
More from this funder
- Funder identifier:
- https://ror.org/01h0zpd94
- Publisher:
- Elsevier
- Journal:
- Mechanical Systems and Signal Processing More from this journal
- Volume:
- 225
- Article number:
- 112280
- Publication date:
- 2025-01-06
- Acceptance date:
- 2024-12-24
- DOI:
- EISSN:
-
1096-1216
- ISSN:
-
0888-3270
- Language:
-
English
- Keywords:
- Pubs id:
-
2077399
- Local pid:
-
pubs:2077399
- Deposit date:
-
2025-01-13
Terms of use
- Copyright holder:
- Elsevier Ltd.
- Copyright date:
- 2024
- Rights statement:
- © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
- Notes:
-
The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford’s Open Access Publications Policy, and a CC BY public copyright licence has been applied.
This is the accepted manuscript version of the article. The final version is available online from Elsevier at https://dx.doi.org/10.1016/j.ymssp.2024.112280
- Licence:
- CC Attribution (CC BY)
If you are the owner of this record, you can report an update to it here: Report update to this record