Triboelectric nanogenerator-based self-powered resonant sensor for non-destructive defect detection.

Chen, Jinkai ORCID: 0000-0002-9409-9632, Zhang, Chi, Xuan, Weipeng, Yu, Liyang, Dong, Shurong ORCID: 0000-0002-8715-7072, Xie, Yuedong ORCID: 0000-0001-9535-0764, Yin, Wuliang and Luo, J. ORCID: 0000-0003-0310-2443 (2019) Triboelectric nanogenerator-based self-powered resonant sensor for non-destructive defect detection. Sensors, 19 (15). ISSN 1424-8220

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Abstract

A triboelectric nanogenerator-based self-powered resonant sensor is proposed and investigated. By integrating an inductor and a microswitch with a triboelectric nanogenerator, a new type triboelectric nanogenerator is obtained, the pulse voltage output is converted to an oscillating signal with a very stable modulated resonant frequency, immune to the cross disturbance of contact-related variation (force, frequency, distance) and environmental variation, such as humidity and temperature. This is utilized for non-destructive defect detection. When the coil inductor scans the surface of a specimen with defects, varying resonant frequencies are obtained for different types of defects, showing excellent consistency between the experimental and simulated results. The results demonstrate the potential of the self-powered TENG-based resonant sensor to be a highly stable and sensitive magnetic sensor for the non-destructive defect detection applications.

Item Type: Article
Uncontrolled Keywords: non-destructive testing, resonant, self-powered sensor, triboelectric
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 04 Feb 2020 10:48
Last Modified: 04 Feb 2020 10:48
Identification Number: 10.3390/s19153262
Funders: ** Funder: the Starting Research Fund from the Hangzhou Dianzi University; Grant(s): KYS045619025, ** Funder: Zhejiang Province Key R & D programs; Grant(s): 2018C01037, ** Funder: National Key R&D program of China; Grant(s): 2018YFB2002500, ** Funder: Zhejiang Lab; Grant(s): 2018EB0ZX01
URI: http://ubir.bolton.ac.uk/id/eprint/2426

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