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A Portable Real-Time Test Bench for Dielectric Elastomer Actuators
- Source :
- Machines, Vol 11, Iss 3, p 380 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- Recently, a significant amount of research has been devoted to soft robots. Artificial muscles belong to the most important components of soft robots. Dielectric elastomer actuators (DEAs) represent the technology that comes closest to the capabilities of a natural muscle, making them the best candidates for artificial muscles in robotics and prosthetics applications. To develop these applications, an analysis of DEAs in a test bench must be possible. It is important that the environmental conditions are known, and all components are specified, which is not the case in most publications. This paper focuses on the development of a real-time test bench for DEAs which provides environmental conditions and all components that are specified. Its goal is to open up the research field of dielectric elastomer actuators or soft robots. The stacked DEA used is powered by a high-voltage amplifier, which can be controlled via a real-time block diagram environment together with a data acquisition (DAQ) device. The response of the actuator is measured with a laser triangulation sensor. Furthermore, information about the applied voltage, the operating current, the temperature, and the humidity are collected. It was demonstrated that the selected laser sensor is a suitable device for this application. Moreover, it was shown that the selected high-voltage amplifier is adequate to power a DEA. However, the DAQ is not fast enough to measure the actuator current. It was demonstrated that housing keeps environmental conditions constant, is transportable, and offers the flexibility to investigate different DEAs.
Details
- Language :
- English
- ISSN :
- 11030380 and 20751702
- Volume :
- 11
- Issue :
- 3
- Database :
- Directory of Open Access Journals
- Journal :
- Machines
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.63513355af444c3d9112f6453bab3eb8
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/machines11030380