Self-Powered Sensor Based on Triboelectric Nanogenerator for Landslide Displacement Measurement

被引:1
作者
Chen, Jinguo [1 ,2 ]
Zou, Hao [1 ,2 ]
Pan, Guangzhi [3 ]
Mao, Shuai [2 ]
Chen, Bing [2 ]
Wu, Chuan [3 ]
机构
[1] Hubei Geol Bur, Hubei Key Lab Resources & Ecoenvironm Geol, Wuhan 430034, Peoples R China
[2] Ctr Geol Environm, Geol Brigade Hubei Geol Bur 3, Huanggang 438000, Peoples R China
[3] China Univ Geosci, Fac Mech & Elect Informat, Wuhan, Peoples R China
关键词
displacement sensor; landslide monitoring; self-powered; triboelectric nanogenerator; ENERGY;
D O I
10.1155/js/6182699
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Landslides are a severe geological disaster that can cause casualties and property damage. Surface deformation displacement monitoring plays a crucial role in landslide monitoring and early warning systems. However, the shortage of power supply at landslide monitoring sites limits the widespread installation of automated landslide displacement monitoring sensors. In this research, we propose a self-powered sensor (displacement monitoring sensor-triboelectric nanogenerator [DIS-TENG]) for monitoring landslide displacement based on the TENG. The DIS-TENG utilizes the principle of frictional electrification and electrostatic induction to convert landslide displacement into voltage signal output, thereby achieving the monitoring of landslide displacement. Test results show that the output voltage of the DIS-TENG is directly proportional to the landslide displacement, and the maximum output voltage is 26.98 V. The measurement range is 1-12 cm, the measurement errors are below 5%, the maximum output power is 9.02 mu W with an external load resistance of 107 ohm, and the sensor operates reliably within a temperature range of 5 degrees C to 85 degrees C and a humidity range of 10%-80%. Compared to traditional landslide displacement monitoring sensors, the DIS-TENG possesses the distinct advantage of not requiring an external power supply. Given the absence of reliable power sources in outdoor working environments, a self-powered sensor is undeniably more suitable for such conditions.
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页数:13
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共 54 条
[1]   Application of advanced technologies in landslide research in the area of the City of Zagreb (Croatia, Europe) [J].
Arbanas, Snjezana Mihalic ;
Krkac, Martin ;
Bernat, Sanja .
GEOLOGIA CROATICA, 2016, 69 (02) :231-243
[2]   Analyzing urbanization induced groundwater stress and land deformation using time-series Sentinel-1 datasets applying PSInSAR approach [J].
Awasthi, Shubham ;
Jain, Kamal ;
Bhattacharjee, Sutapa ;
Gupta, Vivek ;
Varade, Divyesh ;
Singh, Hemant ;
Narayan, Avadh Bihari ;
Budillon, Alessandra .
SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 844
[3]   A Hybrid Early Warning Method for the Landslide Acceleration Process Based on Automated Monitoring Data [J].
Bai, Dongxin ;
Lu, Guangyin ;
Zhu, Ziqiang ;
Zhu, Xudong ;
Tao, Chuanyi ;
Fang, Ji .
APPLIED SCIENCES-BASEL, 2022, 12 (13)
[4]   Worldwide Research Trends in Landslide Science [J].
Carrion-Mero, Paul ;
Montalvan-Burbano, Nestor ;
Morante-Carballo, Fernando ;
Quesada-Roman, Adolfo ;
Apolo-Masache, Boris .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (18)
[5]   A catastrophic natural disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding in Zhejiang Province, China [J].
Cui Yu-long ;
Hu Jun-hong ;
Xu Chong ;
Zheng Jun ;
Wei Jiang-bo .
JOURNAL OF MOUNTAIN SCIENCE, 2021, 18 (08) :2108-2119
[6]   Understanding slow-moving landslide triggering processes using low-cost passive seismic and inclinometer monitoring [J].
Fiolleau, Sylvain ;
Uhlemann, Sebastian ;
Wielandt, Stijn ;
Dafflon, Baptiste .
JOURNAL OF APPLIED GEOPHYSICS, 2023, 215
[7]   Visual interpretation of stereoscopic NDVI satellite images to map rainfall<bold>-</bold>induced landslides [J].
Fiorucci, Federica ;
Ardizzone, Francesca ;
Mondini, Alessandro Cesare ;
Viero, Alessia ;
Guzzetti, Fausto .
LANDSLIDES, 2019, 16 (01) :165-174
[8]   Failure Process Analysis of Landslide Triggered by Rainfall at Volcanic Area: Fangshan Landslide Case Study [J].
Gu, Weiwei ;
Li, Zinan ;
Lin, Cheng ;
Zhang, Faming ;
Dong, Menglong ;
Li, Yukun ;
Liu, Chang .
WATER, 2022, 14 (24)
[9]   Recent Progress on Triboelectric Nanogenerators for Vibration Energy Harvesting and Vibration Sensing [J].
Haroun, Ahmed ;
Tarek, Mohamed ;
Mosleh, Mohamed ;
Ismail, Farouk .
NANOMATERIALS, 2022, 12 (17)
[10]   Triboelectric vibration sensor for a human-machine interface built on ubiquitous surfaces [J].
He, Qiang ;
Wu, Yufen ;
Feng, Zhiping ;
Sun, Chenchen ;
Fan, Wenjing ;
Zhou, Zhihao ;
Meng, Keyu ;
Fan, Endong ;
Yang, Jin .
NANO ENERGY, 2019, 59 :689-696