JOURNAL ARTICLE

Self-sensing McKibben actuators using dielectric elastomer sensors

N. C. GoulbourneSeyul SonJ. W. Fox

Year: 2007 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 6524 Pages: 652414-652414   Publisher: SPIE

Abstract

In this paper, a self-sensing McKibben actuator using dielectric elastomer sensors is presented. Fiber-reinforced cylindrical actuators offer one potential solution to the low-force output problem that plagues many artificial muscle actuators. Placing a cylindrical dielectric elastomer sensor in direct contact with the inner surface of the McKibben actuator facilitates in situ monitoring of actuator strains and loads. The deformation of the McKibben actuator and hence the cylindrical dielectric elastomer sensor results in a change in the electrical signal read from the electroded surfaces of the dielectric elastomer. In this paper, we present a model for predicting the response of fiber reinforced cylindrical constructs (McKibben actuators) that are actuated by an inflation pressure, which is used to support an axial load. The model is based on Adkins and Rivlin's large deformation model for the inflation and contraction of tubes reinforced with inextensible fibers. In this model, the McKibben actuator is considered as a surface of revolution since the initially near cylindrical shape is nearly always compromised during mechanical loading. A series of experiments measuring the force versus contraction behavior of the actuators are used to validate the numerical model. The material constants for an Ogden model were determined by uni-axial extension of cylindrical samples. A comparison of the numerical and experimental results shows that the correlation is good. The model enables a number of key analyses such as the effect of the braid angle and the tension generated in the fibers.

Keywords:
Actuator Materials science Elastomer Artificial muscle Dielectric Composite material Acoustics Computer science Physics Optoelectronics

Metrics

42
Cited By
1.05
FWCI (Field Weighted Citation Impact)
0
Refs
0.76
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Sensor and Energy Harvesting Materials
Physical Sciences →  Engineering →  Biomedical Engineering
Dielectric materials and actuators
Physical Sciences →  Engineering →  Biomedical Engineering
Prosthetics and Rehabilitation Robotics
Physical Sciences →  Engineering →  Biomedical Engineering

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