Prognostics of polygonalization of high-speed railway train wheels using a generalized additive model smoothed by spline-backfitted kernel
2019 (English)In: 2019 IEEE International Conference on Prognostics and Health Management (ICPHM), IEEE, 2019Conference paper, Published paper (Refereed)
Abstract [en]
A method for the prognosis of polygonalization in high-speed railway train wheels is developed based on a generalized additive model. Unlike most previous studies, this study uses field data, so findings can help improve practical maintenance efficiency. A spline-backfitted kernel is used to improve computation efficiency when figuring out model parameters. This prognostics method can be applied to practical railway management decisions.
Place, publisher, year, edition, pages
IEEE, 2019.
Series
International Conference on Prognostics and Health Management, PHM
Keywords [en]
prognostics, preventive maintenance, generalized additive model, spline-backfitted kernel, polygonalization, high-speed railway, train wheels
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-75293DOI: 10.1109/ICPHM.2019.8819407Scopus ID: 2-s2.0-85072762317OAI: oai:DiVA.org:ltu-75293DiVA, id: diva2:1337184
Conference
IEEE International Conference on Prognostics and Health Management (ICPHM2019), 17-20 June, 2019, San Francisco, California, USA
Note
ISBN för värdpublikation: 978-1-5386-8357-6, 978-1-5386-8358-3
2019-07-112019-07-112020-09-16Bibliographically approved