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Enhanced Machine Condition Monitoring Based on Triboelectric Nanogenerator (TENG): A Review of Recent Advancements
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0002-3224-7513
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0002-4271-0380
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0003-3157-4632
School of Material Science and Engineering/Herbert Gleiter Institute of Nanoscience, Nanjing University of Science and Technology, Nanjing, 210094, China.
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2024 (English)In: Advanced Sustainable Systems, E-ISSN 2366-7486, article id 2400575Article, review/survey (Refereed) Epub ahead of print
Abstract [en]

Intelligent machine condition monitoring is desirable to enable Industry 4.0 and 5.0 to create sustainable products and services via the integration of automation, data exchange, and human–machine interface. In the past decades, huge progress has been achieved in establishing sustainable machine condition monitoring systems via various sensing technologies. Yet, the dependence on external power sources or batteries for sensing and data communication remains a challenge. In addition, energy harvesting and sensing are dynamically growing research fields introducing various working mechanisms and designs for improved performance, flexibility, and integrability. Recently, triboelectric nanogenerators (TENG) have been applied as a new technology for energy harvesting and sensing to monitor machine performance. This manuscript presents the potential application of TENG for self-powered sensors and energy harvesting technology for machine condition monitoring, where the developmental aspects of TENG-based devices including the robustness of design and device integration to machine elements are reviewed. For better comparison, the performance of various reported devices is summarized. Simultaneously, the advanced results achieved in employing TENGs for various condition analysis techniques and self-powered wireless communication for machine condition monitoring are discussed. Finally, the challenges, and key strategies for utilizing TENGs for machine condition monitoring in the future, are presented. 

Place, publisher, year, edition, pages
John Wiley and Sons Inc , 2024. article id 2400575
Keywords [en]
condition monitoring, energy harvesting, self-powered, TENG, triboelectric nanogenerator
National Category
Tribology (Interacting Surfaces including Friction, Lubrication and Wear) Energy Engineering
Research subject
Machine Elements
Identifiers
URN: urn:nbn:se:ltu:diva-110240DOI: 10.1002/adsu.202400575ISI: 001319583300001Scopus ID: 2-s2.0-85204779577OAI: oai:DiVA.org:ltu-110240DiVA, id: diva2:1906076
Funder
Swedish Research Council, 2019–04941, 2023–04962
Note

Full text license: CC BY

Available from: 2024-10-16 Created: 2024-10-16 Last updated: 2024-11-20
In thesis
1. Triboelectric Nanogenerator (TENG)-based self-powered machine condition monitoring
Open this publication in new window or tab >>Triboelectric Nanogenerator (TENG)-based self-powered machine condition monitoring
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2024
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Other Mechanical Engineering Energy Engineering
Research subject
Machine Elements
Identifiers
urn:nbn:se:ltu:diva-110048 (URN)978-91-8048-636-1 (ISBN)978-91-8048-637-8 (ISBN)
Public defence
2024-11-29, E246, Luleå University of Technology, Luleå, 09:00 (English)
Opponent
Supervisors
Available from: 2024-09-20 Created: 2024-09-20 Last updated: 2024-11-08Bibliographically approved

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Mehamud, IdirisBjörling, MarcusMarklund, PärShi, Yijun

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