Xu, N. orcid.org/0000-0002-8291-6519, Wang, C. orcid.org/0000-0002-4301-3974, Tang, Y. et al. (2 more authors) (Cover date: May 2024) Constructing wear-sensing coating system with in-service monitoring potential. Tribology International, 193. 109403. ISSN 0301-679X
Abstract
Current wear monitoring approaches estimate the wear status based on indirect sensor signals and early failure detection at component level remains a big challenge. Given this, a novel coating system with built-in wear-sensing capability is developed, which displays strong potential for in-service monitoring and direct implementation on component surfaces. This coating system is composed of top anti-wear layer of diamond-like carbon (DLC) and Raman-sensing under-layer of crystalline silicon. To achieve reliable wear measurement, the impact of deposition parameters on controlling grain growth of silicon sensing layer is thoroughly investigated. The effectiveness in identifying different wear stages and reporting coating failure is fully demonstrated, which can significantly benefit the establishment of predictive maintenance strategies and savings in materials and energy.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 Elsevier Ltd. This is an author produced version of an article published in Tribology International. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Wear sensing, Laser signal, Coating, Life cycle assessment |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Thermofluids, Surfaces & Interfaces (iETSI) (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Functional Surfaces (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Mar 2024 10:52 |
Last Modified: | 07 Feb 2025 01:14 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.triboint.2024.109403 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:209850 |