Whole Life Cycle Monitoring of Landslide Deep Deformation via Triboelectric Nanogenerator

被引:0
|
作者
Liu, Shiming [1 ]
Bi, Xiangzhuang [1 ,2 ]
Zhang, Xiaosong [2 ,3 ]
He, Pengfei [1 ,2 ]
Yang, Yu [2 ]
Li, Hengyu [2 ,3 ,4 ]
Cheng, Xiaojun [2 ,3 ,4 ]
Cheng, Tinghai [2 ,3 ,4 ]
机构
[1] Shenyang Jianzhu Univ, Sch Mech Engn, Shenyang 110168, Peoples R China
[2] Chinese Acad Sci, Beijing Inst Nanoenergy & Nanosyst, Beijing 101400, Peoples R China
[3] Univ Chinese Acad Sci, Sch Nanosci & Engn, Beijing 100049, Peoples R China
[4] Guangzhou Inst Blue Energy, Guangzhou 510555, Peoples R China
基金
中国博士后科学基金; 北京市自然科学基金;
关键词
instantaneous structure; landslide deep monitoring; life cycle; tilt sensors; triboelectric nanogenerators; EARLY IDENTIFICATION; ENERGY;
D O I
10.1002/adfm.202413186
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The displacement monitoring of the slow landslide deep deformation is an important part of the landslide early warning system. However, the traditional energy supply mode of depth sensors limits the large-scale landslide monitoring of the whole life cycle. Therefore, it is necessary to realize self-powered monitoring for deep deformation at extremely low speed. Herein, an extremely low-speed triboelectric tilt sensor (ELS-TTS) is proposed for whole life cycle monitoring of landslide deep deformation without an energy supply. The triboelectric self-sensing unit based on the triboelectric nanogenerator (TENG) and the instantaneous structure of gravity energy storage is designed. A prototype of ELS-TTS with a resolution of 0.075 degrees is fabricated and experimented. ELS-TTS can stably monitor extremely low speeds of below 0.0257 degrees s-1 in different environments and motion states, and the monitoring error is less than 0.13 degrees. Furthermore, a real-time monitoring system for deep landslides based on a multi-level forewarning method is proposed to realize the whole life cycle monitoring of landslides and the multi-level forewarning of dangerous states. This work further promotes the development of TENG in the fields of natural disaster prevention and structural health monitoring.
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页数:12
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