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Enhancing Artificial Lighting Source's Reliability in Public Libraries: Insights into Failure Analysis and Fault Diagnosis
Qingdao University of Science and Technology, College of Electromechanical Engineering, Qingdao, China.
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Luleå University of Technology, Division of Operation and Maintenance, Luleå, Sweden.ORCID iD: 0000-0002-7458-6820
2024 (English)In: 2024 IEEE International Conference on Prognostics and Health Management, ICPHM 2024, Institute of Electrical and Electronics Engineers Inc. , 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
Institute of Electrical and Electronics Engineers Inc. , 2024. p. 231-238
Keywords [en]
artificial lighting sources, failure analysis, fault diagnosis, public libraries, reliability, Lighting, Artificial lighting, Artificial lighting source, Evaluation methods, Faults diagnosis, Lighting technology, Operational conditions, Performance outcome, Public library, Real-world, Reliability Evaluation
National Category
Civil Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-68338DOI: 10.1109/ICPHM61352.2024.10626648ISI: 001298819500030Scopus ID: 2-s2.0-85202346317ISBN: 9798350374476 (print)OAI: oai:DiVA.org:mdh-68338DiVA, id: diva2:1895495
Conference
2024 IEEE International Conference on Prognostics and Health Management, ICPHM 2024, Spokane, June 17-19, 2024
Available from: 2024-09-05 Created: 2024-09-05 Last updated: 2025-10-10Bibliographically approved

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Lin, Jing

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  • apa
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