An analytical model for studying the structural effects and optimization of a capacitive tactile sensor array. (29th February 2016)

• Record Type: Journal Article
• Authors: Liang, Guanhao; Wang, Yancheng; Mei, Deqing; Xi, Kailun; Chen, Zichen
• Is Part Of: Journal of micromechanics and microengineering. Volume 26:Number 4(2016:Apr.)
• Publication Date: 2016-02-29
• Subjects: flexible capacitive tactile sensor -- PDMS truncated pyramid array -- analytical model -- Ritz method; Microelectromechanical systems -- Periodicals; Micromechanics -- Periodicals; 621.38105
• DOI: 10.1088/0960-1317/26/4/045007
• Languages: English
• ISSNs: 0960-1317

Abstract

Abstract: This paper presents an analytical model to study the structural effects of a capacitive tactile sensor array on its capacitance changes and sensitivities. The tactile sensor array has 8 × 8 sensor units, and each unit utilizes the truncated polydimethylsiloxane (PDMS) pyramid array structure as the dielectric layer to enhance the sensing performance. To predict the capacitance changes of the sensor unit, it is simplified into a two-layered structure: upper polyethylene terephthalate (PET) film and bottom truncated PDMS pyramid array. The upper PET is modeled by a displacement field function, while each of the truncated pyramids is analyzed to obtain its stress–strain relation. Using the Ritz method, the displacement field functions are solved. The deformation of the upper electrodes and the capacitance changes of the sensor unit can then be calculated. Using the developed model, the structural effects of the truncated PDMS pyramid array and the PDMS bump on the capacitance changes and sensitivities are studied. To achieve the largest capacitance changes, the dimensions have been optimized for the sensor unit. To verify the developed model, we have fabricated the sensor array, and the average sensitivities of the sensor unit to the x -, y -, and z -axes force are 0.49, 0.50, and 0.32% mN −1, respectively, while the model predicted values are 0.54, 0.54, and 0.35% mN −1 . Results demonstrate that the developed model can accurately predict the sensing performance of the sensor array and could be utilized for structural optimization.