dc.contributor.author |
Ngwangwa, Harry Magadhlela
|
|
dc.contributor.author |
Heyns, P.S. (Philippus Stephanus)
|
|
dc.contributor.author |
Labuschagne, F.J.J. (Kobus)
|
|
dc.contributor.author |
Kululanga, Grant K.
|
|
dc.date.accessioned |
2012-09-14T14:34:04Z |
|
dc.date.available |
2012-09-14T14:34:04Z |
|
dc.date.issued |
2010-04 |
|
dc.description.abstract |
The road damage assessment methodology in this paper utilizes an artificial neural network that reconstructs road surface profiles
from measured vehicle accelerations. The paper numerically demonstrates the capabilities of such a methodology in the presence of noise,
changing vehicle mass, changing vehicle speeds and road defects. In order to avoid crowding out understanding of the methodology, a
simple linear pitch-plane model is employed. Initially, road profiles from known roughness classes were applied to a physical model to
calculate vehicle responses. The calculated responses and road profiles were used to train an artificial neural network. In this way, the
network renders corresponding road profiles on the availability of fresh data on model responses. The results show that the road profiles
and associated defects can be reconstructed to within a 20% error at a minimum correlation value of 94%. |
en_US |
dc.description.librarian |
ai2013 |
|
dc.description.sponsorship |
The Council for Scientific and Industrial
Research (CSIR) and the National Research Foundation
under the South African Co-operation Fund for Scientific
Research and Technological Developments. |
en_US |
dc.description.uri |
http://www.elsevier.com/locate/jterra |
en_US |
dc.identifier.citation |
H.M. Ngwangaw, P.S. Heyns, F.J.J. Labuschagne & G.K. Kululanga, Reconstruction of road defects and road roughness clasification using vehicl responses with artificial neural networks simulation, Journal of Terramechanics, vol. 47, no. 2, pp. 97-111 (2012), doi: 10.1016/j.terra.2009.08.007. |
en_US |
dc.identifier.issn |
0022-4898 (print) |
|
dc.identifier.issn |
1879-1204 (online) |
|
dc.identifier.other |
10.1016/j.terra.2009.08.007 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/19779 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
Elsevier |
en_US |
dc.rights |
© 2009 ISTVS. Published by Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Journal of Terramechanics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal
of Terramechanics, vol. 47, no. 2, pp. 97-111 (2012), doi: 10.1016/j.terra.2009.08.007. |
en_US |
dc.subject |
Reconstruction of road defects |
en_US |
dc.subject |
Road roughness classification |
en_US |
dc.subject |
Artificial neural networks simulation |
en_US |
dc.subject |
Vehicles |
en_US |
dc.subject.lcsh |
Pavements -- Defects |
en |
dc.subject.lcsh |
Pavements -- Live loads |
en |
dc.subject.lcsh |
Pavements -- Service life |
en |
dc.subject.lcsh |
Roads -- Design and construction |
en |
dc.subject.lcsh |
Neural networks (Computer science) |
en |
dc.title |
Reconstruction of road defects and road roughness classification using vehicle responses with artificial neural networks simulation |
en_US |
dc.type |
Postprint Article |
en_US |