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Grey-system-theory-based model for the prediction of track geometry quality
School of Civil Engineering, Beijing Jiaotong University, People’s Republic of China.
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.ORCID-id: 0000-0001-9843-5819
School of Civil Engineering, Beijing Jiaotong University, People’s Republic of China.
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
Vise andre og tillknytning
Rekke forfattare: 52016 (engelsk)Inngår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, nr 7, s. 1735-1744Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The quality of track geometry is an important aspect in railway engineering, as it reflects any deviations and thus the actual condition of a track. Monitoring and prediction of a relevant geometry quality parameter provides an opportunity for effective maintenance, thus creating the advantages of extending the life of the asset, reducing maintenance costs and minimizing possession time requirements. Effective maintenance practice requires a good understanding of the behaviour of track structures over time and also prediction of its condition using only a few inputs. This paper presents a grey-system-theory-based model for predicting track irregularity. Three variants of the grey model are presented and their performances are compared with simple linear and exponential models. Regression models and the grey-system-theory-based models are used to obtain the standard deviation of the longitudinal level from a series of geometry inspection data. The overall performances of the models are evaluated in terms of the regression and prediction accuracies, and it is shown that a Fourier series modification of the grey model has the best performance and the minimum error. The contribution of this paper is the creation of a prediction model for track geometry quality, which is essential for planning and scheduling of preventive geometry maintenance.

sted, utgiver, år, opplag, sider
2016. Vol. 230, nr 7, s. 1735-1744
HSV kategori
Forskningsprogram
Drift och underhållsteknik
Identifikatorer
URN: urn:nbn:se:ltu:diva-10513DOI: 10.1177/0954409715610603ISI: 000382571800009Scopus ID: 2-s2.0-84981334973Lokal ID: 9532944f-68c3-48e5-80fe-2c1aff1b0c15OAI: oai:DiVA.org:ltu-10513DiVA, id: diva2:983458
Merknad

Validerad; 2016; Nivå 2; 20151029 (stefam)

Tilgjengelig fra: 2016-09-29 Laget: 2016-09-29 Sist oppdatert: 2018-07-10bibliografisk kontrollert

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