State space mathematical modeling for mechanoelectrical transduction of Polyvinyl Chloride (PVC) based sensors

Justin Neubauer; Kwang Jin Kim

doi:10.1117/12.2584504

22 March 2021 State space mathematical modeling for mechanoelectrical transduction of Polyvinyl Chloride (PVC) based sensors

Justin Neubauer, Kwang Jin Kim

Author Affiliations +

Proceedings Volume 11587, Electroactive Polymer Actuators and Devices (EAPAD) XXIII; 115870L (2021) https://doi.org/10.1117/12.2584504
Event: SPIE Smart Structures + Nondestructive Evaluation, 2021, Online Only

Abstract

Polyvinyl chloride (PVC) gels have been studied in some detail and exhibit mechanoelectrical transduction properties, making these materials suitable for sensing applications. This study aims to investigate these mechanoelectrical properties through mathematical modeling. A nonlinear gray-box hybrid state space approach can accurately model the mechanoelectrical transduction properties of the PVC gel sensor in both transient and steady state responses. This approach studies multiple nonlinearities in both transient and steady state mechanoelectrical responses such as overshoot variation and signal attenuation. Mechanoelectrical polarity inversion for tensile/compressive loading schemes exhibited in experimental testing is also investigated in the nonlinear model. A simplified linearized model also shows accurate results for the linear region of mechanoelectrical responses in the PVC gel sensors. Further mathematical modeling aims to describe some underlying physics and governing equations of the mechanoelectrical properties of PVC gel sensors.

Conference Presentation

Citation Download Citation

Justin Neubauer and Kwang Jin Kim "State space mathematical modeling for mechanoelectrical transduction of Polyvinyl Chloride (PVC) based sensors", Proc. SPIE 11587, Electroactive Polymer Actuators and Devices (EAPAD) XXIII, 115870L (22 March 2021); https://doi.org/10.1117/12.2584504

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available