A Self‐Powered Dual‐Type Signal Vector Sensor for Smart Robotics and Automatic Vehicles. Issue 14 (26th February 2022)

• Record Type: Journal Article
• Authors: Li, Shaoxin; Zhao, Zhihao; Liu, Di; An, Jie; Gao, Yikui; Zhou, Linglin; Li, Yanhong; Cui, Shengnan; Wang, Jie; Wang, Zhong Lin
• Is Part Of: Advanced materials. Volume 34:Issue 14(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-26
• Subjects: automatic robotics -- automatic vehicles -- real‐time monitoring vector movement -- self‐powered vector sensors -- triboelectric nanogenerators; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adma.202110363
• Languages: English
• ISSNs: 0935-9648

Abstract

Abstract: Automatic control systems are the most efficient technology for reducing labor cost while improving work efficiency. Vector motion monitoring is indispensable for the normal operation of automatic control systems. Here, a self‐powered dual‐type signal triboelectric nanogenerator (DS‐TENG) is designed through integrating an alternating‐current TENG and a direct‐current TENG, which can monitor vector movement in real time based on pulse signal counts. As a result, the DS‐TENG avoids the shortcoming of traditional self‐powered sensors based on signal amplitude that is sensitive to the working environment, achieves a high sensing precision, and maintains stability after reciprocating motion of 500 000 cycles. Moreover, it realizes effective movement direction recognition by self‐powered switching of signal type in reverse movement. This dual‐type signal TENG exhibits high precision and automatic direction recognition in vector motion monitor and trajectory tracker, paving the way for the application of the self‐powered TENG sensor in automatic control systems in the future. Abstract : A self‐powered dual‐type signal vector sensor is designed by integrating an alternating‐current triboelectric nanogenerator (TENG) and a direct‐current TENG, which achieves a high sensing precision and stability, and provides an effective movement direction recognition method by self‐powered switching of signal type in real‐time motion monitoring of a mechanical arm and automatic steering wheel.