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Enhancing Artificial Lighting Source’s Reliability in Public Libraries: Insights into Failure Analysis and Fault Diagnosis
College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao, China.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Division of Product Realization, Mälardalen University, Eskilstuna, Sweden.ORCID iD: 0000-0002-7458-6820
2024 (English)In: 2024 IEEE International Conference on Prognostics and Health Management (ICPHM), IEEE, 2024, p. 231-238Conference paper, Published paper (Refereed)
Abstract [en]

Despite the advancements in artificial lighting technology, such as LEDs, a gap persists between expected and actual performance outcomes, attributed to conventional reliability evaluation methods that inadequately mirror real-world operational conditions. This study explores the crucial roles of failure analysis and fault diagnosis in improving lighting source reliability. It reveals a focus on LED lighting failure analysis based on test data, highlighting a disconnect from operational fault diagnosis. By detailing fault types and diagnostic tools, the study proposes a practical fault diagnosis framework. This framework aims to enhance lighting reliability by incorporating diagnostic insights back into the design and manufacturing stages, creating a closed-loop system between failure analysis and fault diagnosis. This approach bridges the gap between theory and practice, advancing lighting reliability in public libraries. However, the insights into failure analysis and fault diagnosis can be applied to other scenarios.

Place, publisher, year, edition, pages
IEEE, 2024. p. 231-238
Keywords [en]
artificial lighting sources, reliability, failure analysis, fault diagnosis, public libraries
National Category
Other Civil Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-109764DOI: 10.1109/ICPHM61352.2024.10626648ISI: 001298819500030Scopus ID: 2-s2.0-85202346317OAI: oai:DiVA.org:ltu-109764DiVA, id: diva2:1895841
Conference
2024 IEEE International Conference on Prognostics and Health Management (ICPHM), Spokane, WA, USA, June 17-19, 2024
Funder
Swedish Energy Agency
Note

ISBN for host publication: 979-8-3503-7447-6

Available from: 2024-09-07 Created: 2024-09-07 Last updated: 2025-04-03Bibliographically approved

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Lin, Jing (Janet)

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CiteExportLink to record
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  • apa
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