摘要
In this paper,a structural analysis is performed to gain insights on the synergistic mechanical amplification effect thatCampaniform sensilla have when combined in an array configuration.In order to simplify the analysis performed in this preliminaryinvestigation,an array of four holes in a single orthotropic lamina is considered.Firstly,a Finite Element Method(FEM) analysis is performed to discretely assess the influence that different geometrical parameters have on the mechanicalamplification properties of the array.Secondly,an artificial neural network is used to obtain an approximated multi-dimensionalcontinuous function,which models the relationship between the geometrical parameters and the amplification properties of thearray.Thirdly,an optimization is performed to identify the geometrical parameters yielding the maximum mechanical amplification.Finally,results are validated with an additional FEM simulation performed by varying geometrical parameters in theneighborhood of the identified optimal parameters.The method proposed in this paper can be fully automated and used to solvea wide range of optimization problems aimed at identifying optimal configurations of strain sensors inspired by Campaniformsensilla.
In this paper,a structural analysis is performed to gain insights on the synergistic mechanical amplification effect thatCampaniform sensilla have when combined in an array configuration.In order to simplify the analysis performed in this preliminaryinvestigation,an array of four holes in a single orthotropic lamina is considered.Firstly,a Finite Element Method(FEM) analysis is performed to discretely assess the influence that different geometrical parameters have on the mechanicalamplification properties of the array.Secondly,an artificial neural network is used to obtain an approximated multi-dimensionalcontinuous function,which models the relationship between the geometrical parameters and the amplification properties of thearray.Thirdly,an optimization is performed to identify the geometrical parameters yielding the maximum mechanical amplification.Finally,results are validated with an additional FEM simulation performed by varying geometrical parameters in theneighborhood of the identified optimal parameters.The method proposed in this paper can be fully automated and used to solvea wide range of optimization problems aimed at identifying optimal configurations of strain sensors inspired by Campaniformsensilla.
基金
supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada and CMC Microsystems
