High-Performance Bionic Tactile Sensing Method for Temperature and Pressure Based on Triboelectric Nanogenerator and Micro-Thermoelectric Generator

IF 4.9 3区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY
Changxin Liu, Runhe Chen, Peihan Huang, Guangyi Xing, Zhijie Hao, Haoxuan Che, Dazhi Zhang, Rongxin Zhang, Mingyu Lu
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Abstract

In intricate aquatic environments, enhancing the sensory performance of underwater actuators to ensure successful task execution is a significant challenge. To address this, a biomimetic tactile multimodal sensing approach is introduced in this study, based on TriboElectric NanoGenerator (TENG) and Micro-ThermoElectric Generator (MTEG). This method enables actuators to identify the material properties of underwater target objects and to sense grasping states, such as pressure and relative sliding. In this study, a multi-dimensional underwater bionic tactile perception theoretical model is established, and a bionic sensing prototype with a sandwich-type structure is designed. To verify the performance of pressure feedback and material perception, pertinent experiments are conducted. The experimental results reveal that within a pressure measurement range of 0–16 N, the detection error of the sensor is 1.81%, and the maximum pressure response accuracy achieves 2.672 V/N. The sensing response time of the sensor is 0.981 s. The recovery time of the sensor is 0.97 s. Furthermore, the exceptional fatigue resistance of the sensor is also demonstrated. Based on the frequency of the output voltage from the prototype, the sliding state of the target object relative to the actuator can be sensed. In terms of material identification, the temperature response accuracy of the sensor is 0.072 V/°C. With the assistance of machine learning methods, six characteristic materials are identified by the sensor under 7 N pressure, with a recognition accuracy of 92.4%. In complex marine environments, this method has great application potential in the field of underwater tactile perception.

基于摩擦电纳米发电机和微热电发电机的高性能温度和压力仿生触觉传感方法
在复杂的水生环境中,提高水下执行器的感官性能以确保任务的成功执行是一项重大挑战。为了解决这一问题,本研究介绍了一种基于摩擦电纳米发电机(TENG)和微热电发电机(MTEG)的仿生触觉多模态传感方法。该方法使执行器能够识别水下目标物体的材料特性,并感知抓取状态,如压力和相对滑动。本研究建立了多维水下仿生触觉感知理论模型,设计了三明治式结构仿生触觉感知样机。为了验证压力反馈和材料感知的性能,进行了相应的实验。实验结果表明,在0 ~ 16 N的压力测量范围内,该传感器的检测误差为1.81%,最大压力响应精度达到2.672 V/N。传感器的传感响应时间为0.981 s。传感器的恢复时间为0.97 s。此外,还证明了该传感器具有优异的抗疲劳性能。基于原型输出电压的频率,可以感知目标物体相对于执行器的滑动状态。在材料识别方面,传感器的温度响应精度为0.072 V/°C。借助机器学习方法,传感器在7 N压力下识别出6种特征材料,识别准确率达到92.4%。在复杂的海洋环境中,该方法在水下触觉感知领域具有很大的应用潜力。
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来源期刊
Journal of Bionic Engineering
Journal of Bionic Engineering 工程技术-材料科学:生物材料
CiteScore
7.10
自引率
10.00%
发文量
162
审稿时长
10.0 months
期刊介绍: The Journal of Bionic Engineering (JBE) is a peer-reviewed journal that publishes original research papers and reviews that apply the knowledge learned from nature and biological systems to solve concrete engineering problems. The topics that JBE covers include but are not limited to: Mechanisms, kinematical mechanics and control of animal locomotion, development of mobile robots with walking (running and crawling), swimming or flying abilities inspired by animal locomotion. Structures, morphologies, composition and physical properties of natural and biomaterials; fabrication of new materials mimicking the properties and functions of natural and biomaterials. Biomedical materials, artificial organs and tissue engineering for medical applications; rehabilitation equipment and devices. Development of bioinspired computation methods and artificial intelligence for engineering applications.
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