dc.contributor.author |
Heyns, T
|
|
dc.contributor.author |
Heyns, PS
|
|
dc.contributor.author |
De Villiers, JP
|
|
dc.date.accessioned |
2013-03-25T07:14:23Z |
|
dc.date.available |
2013-03-25T07:14:23Z |
|
dc.date.issued |
2012-04 |
|
dc.identifier.citation |
Heyns, T, Heyns, PS and DE Villers, JP. 2012. A method for real-time condition monitoring of haul roads based on Bayesian parameter estimation. Journal of Terramechanics, vol. 49(2), pp. 103-113 |
en_US |
dc.identifier.issn |
0022-4898 |
|
dc.identifier.uri |
http://www.sciencedirect.com/science/article/pii/S0022489811001029
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|
dc.identifier.uri |
http://hdl.handle.net/10204/6625
|
|
dc.description |
Copyright: 2011 ISTVS. Published by Elsevier. This is the preprint version of the work. The definitive version is published in Journal of Terramechanics, vol. 49(2), pp. 103-113 |
en_US |
dc.description.abstract |
Current haul road management techniques, such as routine, periodic and urgent maintenance have shortcomings in many complex haul road environments. Real-time road condition monitoring may significantly reduce maintenance costs, both to the road and to the vehicles. A recent idea is that vehicle on-board data collection systems could be used to monitor haul roads on a real-time basis by means of vibration signature analysis. This paper proposes a methodology based on Bayesian regression to isolate the effect of varying vehicle speed on the measured vehicle response metric. A key feature of the proposed methodology is that it avoids the costly need to generate analytical or empirical vehicle models. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Elsevier |
en_US |
dc.relation.ispartofseries |
Workflow;7721 |
|
dc.relation.ispartofseries |
Workflow;10223 |
|
dc.subject |
Road condition monitoring |
en_US |
dc.subject |
Bayesian parameter estimation |
en_US |
dc.subject |
Condition based maintenance |
en_US |
dc.title |
A method for real-time condition monitoring of haul roads based on Bayesian parameter estimation |
en_US |
dc.type |
Article |
en_US |
dc.identifier.apacitation |
Heyns, T., Heyns, P., & De Villiers, J. (2012). A method for real-time condition monitoring of haul roads based on Bayesian parameter estimation. http://hdl.handle.net/10204/6625 |
en_ZA |
dc.identifier.chicagocitation |
Heyns, T, PS Heyns, and JP De Villiers "A method for real-time condition monitoring of haul roads based on Bayesian parameter estimation." (2012) http://hdl.handle.net/10204/6625 |
en_ZA |
dc.identifier.vancouvercitation |
Heyns T, Heyns P, De Villiers J. A method for real-time condition monitoring of haul roads based on Bayesian parameter estimation. 2012; http://hdl.handle.net/10204/6625. |
en_ZA |
dc.identifier.ris |
TY - Article
AU - Heyns, T
AU - Heyns, PS
AU - De Villiers, JP
AB - Current haul road management techniques, such as routine, periodic and urgent maintenance have shortcomings in many complex haul road environments. Real-time road condition monitoring may significantly reduce maintenance costs, both to the road and to the vehicles. A recent idea is that vehicle on-board data collection systems could be used to monitor haul roads on a real-time basis by means of vibration signature analysis. This paper proposes a methodology based on Bayesian regression to isolate the effect of varying vehicle speed on the measured vehicle response metric. A key feature of the proposed methodology is that it avoids the costly need to generate analytical or empirical vehicle models.
DA - 2012-04
DB - ResearchSpace
DP - CSIR
KW - Road condition monitoring
KW - Bayesian parameter estimation
KW - Condition based maintenance
LK - https://researchspace.csir.co.za
PY - 2012
SM - 0022-4898
T1 - A method for real-time condition monitoring of haul roads based on Bayesian parameter estimation
TI - A method for real-time condition monitoring of haul roads based on Bayesian parameter estimation
UR - http://hdl.handle.net/10204/6625
ER -
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en_ZA |