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Piezoresistive sensor fiber composites based on silicone elastomers for the monitoring of the position of a robot arm

机译:压阻式传感器纤维复合材料,基于硅氧烷弹性体监测机器人臂的位置

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摘要

Combining conductive fillers like carbon black with elastomers allows the development of soft elastomer strain sensors that can reach very large elongations, an important requirement for many robotic applications. However, when the conductive filler is introduced in the polymer, significant stiffening occurs, affecting the mechanical properties, e.g. Young's Modulus, of the soft structure. In this attempt, single piezoresistive fiber composites were successfully fabricated, without drastically increasing the stiffness. Two silicone elastomers that are widely used in robotic applications were examined as matrix materials. Furthermore, modeling the stresses exerted on the fiber inside the composite was successfully used to predict the detachment of fiber inside the matrix, observed by visual inspection. For the PDMS based composite, pre-straining improved sensor properties, which could be confirmed for the monitoring of the movement of the crane robot. The results showed that the pre-strained piezoresistive sensor fiber-matrix composites positions of the robot crane can be monitored even at low strains. (C) 2020 The Authors. Published by Elsevier B.V.
机译:将炭黑等导电填料与弹性体相结合,可以开发软弹性体应变传感器,可以达到非常大的拉伸,这是许多机器人应用的一个重要要求。然而,当在聚合物中引入导电填料时,会发生显著的硬化,从而影响软结构的机械性能,例如杨氏模量。在这一尝试中,在不大幅增加刚度的情况下,成功地制备了单压阻纤维复合材料。研究了两种广泛应用于机器人应用的硅橡胶作为基体材料。此外,模拟施加在复合材料内部纤维上的应力成功地用于预测通过目视检查观察到的基体内部纤维的分离。对于基于PDMS的复合材料,预应变改善了传感器的性能,这可用于监测起重机机器人的运动。结果表明,即使在低应变情况下,也可以监测机器人起重机的预应变压阻传感器纤维基复合材料位置。(C) 2020年,作者。由Elsevier B.V.出版。

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