基于节点分类方法的力敏传感器内部导电网络的动态研究

Dynamic Research on the Internal Conductive Network of Flexible Sensor Based on the Node Classification Method

近年来,橡胶力敏传感器在人体穿戴设备、压力测量、智能机器人等方面有着重要的应用。力敏传感器的力灵敏度是衡量力敏传感器性能优劣的关键。针对以橡胶为基底,碳纳米管(CNTs)为填料所构成的力敏传感器,设计一个适宜的3D模型以模拟力敏传感器受力过程中的动态变化。模拟方法中采用蒙特卡洛随机生成方法以合理模拟传感器的填料的分布,对于传感器电阻的求解使用了基尔霍夫电流定律精准求解。提出节点分类方法来得到传感器灵敏度在结构上的衡量标准。结论是传感器的灵敏度可以通过两类节点的数量差来衡量。

In recent years,rubber flexible sensors have been widely used in wearable devices,pressure measurements,intelligent robots and other fields.The strain sensitivity of flexible sensor is the key to measure the performance.A suitable 3 D model is designed to simulate the dynamic changes of the flexible-sensitive sensor with rubber as the substrate and Carbon Nanotubes(CNTs)as the filler.In the simulation method,the Monte Carlo random generation method is used to reasonably simulate the distribution of the filler,and Kirchhoff’s current law is used to accurately calculate the sensor resistance.A node classification method is proposed to obtain the standard of strain sensitivity in structure.The conclusion is that the sensitivity of the sensor can be measured by the difference in the number of nodes between the two types.