基于压电薄膜传感器的触觉信息采集系统OA
Tactile Information Acquisition System Based on Piezoelectric Film
为了使仿生机械模拟人类利用触觉感知物体表面信息,依据PVDF(Polyvinylidene Fluoride)压电薄膜的压电效应与热释电效应,设计并搭建了一套多触觉信息采集系统,实现了对物体硬度、粘度、湿度、粗糙度以及温度等多种触觉信息的采集和识别.该采集系统将PVDF压电薄膜粘贴在橡胶半球表面制作触觉传感器,使用单片机控制升降台和丝杠滑台带动物体按压和摩擦触觉传感器,有效采集到物体的触觉信息.通过对采集信号的特征值进行分析,建立了粘度和温度的数学模型,粘度和温度灵敏度分别为-2 730 V/m2和0.984 mV/℃.使用方差有效表征了物体的硬度,通过建立BP(Back Propagation)神经网络,实现对湿度和粗糙度90%以上预测成功率.
In order to make bionic machine simulate human sense of touch to perceive the surface information of objects,according to the piezoelectric effect and pyroelectric effect of PVDF(Polyvinylidene Fluoride)piezoelectric film,a set of multi-tactile information acquisition system is designed and built,realizing the collection and recognition of various tactile information such as hardness,viscosity,humidity,roughness and temperature of objects.The PVDF piezoelectric film is pasted on the surface of the rubber hemisphere to make a tactile sensor,a single-chip microcomputer is used to control the lifting table and the lead screw slide table to drive the object to press and friction the tactile sensor,effectively collecting the tactile information of the object,and establisheing a mathematical model of viscosity and temperature by using the eigenvalues of the collected signal for analysis.The viscosity and temperature sensitivity are-2 730 V/m2 and 0.984 mV/℃ respectively,the hardness of the object is effectively characterized by variance,and the success rate of predicting humidity and roughness of more than 90%is achieved by establishing a BP(Back Propagation)neural network.
辛毅;刘宁;翟芸生;宋金洋
吉林大学 仪器科学与电气工程学院,长春 130061吉林大学 仪器科学与电气工程学院,长春 130061吉林大学 仪器科学与电气工程学院,长春 130061吉林大学 仪器科学与电气工程学院,长春 130061
信息技术与安全科学
PVDF压电薄膜触觉智能触觉信息采集BP神经网络ADAM算法
polyvinylidene fluoride(PVDF)piezoelectric filmtactile intelligencetactile information acquisitionback propagation(BP)neural networkadaptive moment estimation
《吉林大学学报(信息科学版)》 2026 (3)
543-550,8
国家重点研发计划基金资助项目(2022YFE0103800)吉林大学大学生创新基金资助项目(202310183259)
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