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Current practices and new approaches within condition monitoring of gravel roads
Linnaeus University, Faculty of Technology, Department of Mechanical Engineering. (HUG;DISA-SIG)ORCID iD: 0000-0002-2637-6175
Linnaeus University, Faculty of Technology, Department of Informatics. (HUG)ORCID iD: 0000-0001-7048-8089
Linnaeus University, Faculty of Technology, Department of Mechanical Engineering. (HUG;DISA-SIG)ORCID iD: 0000-0001-7732-1898
2020 (English)In: International Journal of COMADEM, ISSN 1363-7681, Vol. 23, no 4, p. 3-8Article in journal (Refereed) Published
Abstract [en]

High quality information is essential for the efficient decision making. Road condition is, together with traffic frequency, commonly used as input forclassifying road status. Road condition is also a major input for the maintenance executor (vehicle operator) when deciding on maintenance actions, such asamount of gravel to replenish. With better condition related information, the maintenance execution as well as maintenance planning could be greatlyimproved. The current deficiencies in gravel road condition monitoring methods and technologies are described in this paper, and an approach for objectivemeasurement of gravel road condition is proposed, including new measurement techniques and systems as well as information processing for decision making.This is realized by utilizing research findings from the area of signal processing, maintenance engineering, and information systems engineering in the specificcontext of gravel road monitoring, thus utilizing available technologies and methods as well as physics.

Place, publisher, year, edition, pages
COMADEM International, 2020. Vol. 23, no 4, p. 3-8
Keywords [en]
Gravel road maintenance, Condition monitoring, Signal processing, Structural mechanics, Measurement technique, Information system engineering
National Category
Reliability and Maintenance
Research subject
Technology (byts ev till Engineering), Terotechnology; Technology (byts ev till Engineering), Mechanical Engineering; Computer and Information Sciences Computer Science, Information Systems
Identifiers
URN: urn:nbn:se:lnu:diva-98586Scopus ID: 2-s2.0-85097584550OAI: oai:DiVA.org:lnu-98586DiVA, id: diva2:1477560
Funder
The Kamprad Family Foundation, 20180275Available from: 2020-10-19 Created: 2020-10-19 Last updated: 2022-04-12Bibliographically approved

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Kans, MirkaCampos, JaimeHåkansson, Lars

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