基于埋入式石墨烯压阻传感器的碳纤维机械臂结构健康及振动监测

MONITORING VIBRATION AND STRUCTURE HEALTH OF LIGHTWEIGHT ROBOT USING GRAPHENEBASED NANOCOMPOSITE SENSORS

王青青

11930208

硕士

材料工程

周利民

2021-05-23

2021-06-15

南方科技大学

深圳

传统工业机器人正在被能耗更低、更灵活的轻量化机器人所代替，性能优良的新型复合材料吸引着众多企业和学者对碳纤维复合材料轻量化机器人进行投资和研究。由于碳纤维结构性质导致机器人关节的刚度降低，从而导致操作精度下降。使用传感器测量振动传输给控制器对振动补偿来保证机器人精度。现在很多新型功能复合材料作为传感器安装在结构表面，监测结构健康和振动的研究已经应用在各个领域，但该方法由于粘接不牢和导线的干扰限制了其测量精度。在本文的研究中，开发了一种新型石墨烯环氧树脂传感器与复合材料一体化成型的制造方法，并制作出具有感应能力的智能复合材料机械臂用于轻量化机器人的结构健康和振动监测。石墨烯作为纳米填料均匀分散在环氧树脂基体中，使用模具将该均匀混合物在复合材料板/管的层间特定位置形成一定形状的传感器涂层并接入CNT fiber 传输信号，然后整体固化形成智能复合材料板/管。该传感器的感应原理是隧穿效应，当智能结构感应到振动或者微小应变时传感器中相邻石墨烯片的距离会发生变化导致阻值变化。根据渗透阈值理论和实验分析得出当石墨烯在环氧树脂中的质量分数大约达到1.5% 时，传感器的导电性能急剧增加。通过对比传感器贴在结构表面和嵌入到结构内部对振动的响应，嵌入式传感器频率测量精度提高了50%，测量所得信号强度是传统表贴式测量的3 倍，嵌入式传感器受到更少的外界干扰，能对微小振动和应变做出响应。对比石墨烯环氧树脂传感器与在金属应变片，在高频段（100KHz 以上）石墨烯环氧树脂传感器响应信号远超过应变片；在低频段（<1000Hz）石墨烯环氧树脂传感器响应信号约是应变片的2 倍。本文还对嵌入传感器的智能复材平板和智能复材圆管进行了低频振动（30020000Hz）响应测试，它们都展现出了优秀的响应能力，可测试的频率高达600KHz。将传感器安装在轻量化机器人上测试所得的振动信号与加速度传感器所测信号一致。

Traditional industrial robots are being replaced by lightweight robots with lower energy consumption and more flexibility. New composite materials with excellent performance attract many enterprises and scholars to invest and study lightweight robots made of carbon fiber composite materials. Due to the structural properties of carbon fiber, the stiffness of robot joints decreases, which leads to the decrease of operation accuracy. The vibration measured by the sensor is transmitted to the controller to compensate the vibration to ensure the accuracy of the robot. At present, many new functional composite materials are installed on the surface of structures as sensors, and the research on monitoring structural health and vibration has been applied in various fields. However, the measurement accuracy of this method is limited due to weak bonding and interference of wires. In the research of this paper, a manufacturing method of integrated molding of sensors(new grapheneepoxy resin) and composite materials is developed, and an intelligent composite manipulator with sensing capability is manufactured for structural health and vibration monitoring of lightweight robots. Graphene is uniformly dispersed in the epoxy resin matrix as a nano filler, and the uniform mixture is formed into a sensor coating with a certain shape at a specific position between the layers of the composite plate/tube by a mold and connected into CNT fiber to transmit signals, and then the intelligent composite plate/tube is formed by integral curing. The sensing principle of the sensor is tunneling effect. When the intelligent structure senses vibration or slight strain, the distance between adjacent graphene sheets in the sensor will change, resulting in resistance change. According to the permeation threshold theory and experimental analysis, it is concluded that when the mass fraction of graphene in epoxy resin reaches about 1.5%, the conductivity of the sensor increases sharply. By comparing the vibration response of the sensor attached to the structure surface and embedded in the structure, the frequency measurement accuracy of the embedded sensor is improved by 50%, the measured signal strength is 3 times that of the traditional surfacemounted measurement, the embedded sensor is less disturbed by the outside world, and can respond to small vibration and strain. Comparing grapheneepoxyresin sensor with piezoelectric ceramic sensor, grapheneepoxy resin sensor has fast response speed and signal strength twice that of PZT in high frequency band (above 100KHz). In this paper, the lowfrequency vibration (30020000Hz) response tests of the intelligent composite plate and the intelligent composite tube embedded with the sensor are also carried out, both of which show excellent lower response capability. The intelligent composite material can measure a frequency of up to 600KHz. The vibration signal obtained by installing the sensor on a lightweight robot is consistent with the signal measured by the acceleration sensor.

工业机器人 结构健康检测 纳米复合材料 石墨烯 振动测试

industrial robot structure health monitor nanocomposite graphene vibration test

中文

独立培养

南方科技大学

王青青. 基于埋入式石墨烯压阻传感器的碳纤维机械臂结构健康及振动监测[D]. 深圳. 南方科技大学,2021.