Eur. Phys. J. Appl. Phys.
Volume 69, Number 1, January 2015
|Number of page(s)||11|
|Section||Instrumentation and Metrology|
|Published online||27 January 2015|
Modeling and analysis of electrostatic adhesion force for climbing robot on dielectric wall materials
College of Optoelectronic Engineering, Key Lab of Optoelectronic Technology and Systems of Ministry of Education,Chongqing University, Chongqing
400044, P.R. China
2 College of Mathematics and Statistics, Chongqing University, Chongqing 400044, P.R. China
a e-mail: email@example.com
Revised: 9 December 2014
Accepted: 24 December 2014
Published online: 27 January 2015
In recent years, electrostatic adhesion technology on the wall climbing robots has attracted many researchers interest for its outstanding characteristics. In this paper, a theoretical analytical model is derived from the electrostatic adhesion field between the dielectric wall and a coplanar array of parallel strip electrodes called inter-digital electrodes (IDE). Due to the polarization on the different dielectric being complicated, the field is divided into four layers in order to obtain corresponding boundaries. Besides, the roughness of the wall surface, alternately polarities applied voltages and different dielectric parameter with different layer, all of which are also taken into account in the model since they have a significant influence on the electrostatic adhesion field. Based on this model, the electrostatic adhesion force (EAF) is calculated utilizing the Maxwell stress tensor (MST) formulation. As we all known, EAF is vital to the climbing robot design. Specially, it is possible for us to optimize the load to weight ratio in next step. Through comparing the finite element method (FEM) simulation with theoretical computation, the simulation and calculated data show that our proposed scheme can achieve desired results. Moreover, experiments of electrostatic adhesion performance for the adhesive on some different dielectric materials are also implemented.
© EDP Sciences, 2015
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.