Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6956404 | Mechanical Systems and Signal Processing | 2015 | 14 Pages |
Abstract
Adhesive interactions between surfaces have many engineering implications, since they may be exploited to promote joining between bodies but may also jeopardize the functionality of mechanical systems, when they affects surfaces subjected to relative motion. In some applications the interest arises to develop a model which makes it possible to predict the force required to separate two adhered bodies, given the properties of the materials and of the surfaces. Recent advances in the experimental study of metallic adhesion between engineering metallic surfaces lead to a more detailed investigation, where two main improvements are sought. First, the behaviour of the adhesive bonds is studied in dynamic conditions, i.e. when the separation between the adhered surfaces cannot be considered quasi-static. Second, not only the pull-off force but the complete behaviour of the adhesive bonds as a function of the separation between the surfaces is studied. Both aspects are involved in a dedicated experiment, in which adhesion force rules the transfer of momentum between two bodies if one of them is actuated to perform a dynamic separation. The test facility has been recently developed in order to provide a more representative experiment of the case of study, and a more complex measurement system is available to describe the dynamics of the adhesive bonds. The drawback of the evolution of the experiment is the presence of larger systematic effects and a more difficult estimation of adhesion from the experimental data. Therefore, in order to study and separate the behaviour of adhesion from disturbance effects, a specific grey-box estimation procedure has been set up. Thanks to the improved measurement system, the result of this method is the adhesion force as a function of elongation of the bonds, estimated with a better accuracy than that achieved before. The mathematical model, the regression procedure and the results are here presented and discussed.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
D. Bortoluzzi, C. Zanoni, S. Vitale,