Ngwangwa, HMHeyns, PSLabuschagne, FJJKululanga, GK2008-08-272008-08-272008-07Ngwangwa, HM et al. 2008. Overview of the neural network based technique for monitoring of road condition via reconstructed road profiles. Partnership for research and progress in Transportation. 27th Southern African Transport Conference (SATC), Pretoria, South Africa, July 7-11, 2008, pp 312-329978-1-920017-34-7http://hdl.handle.net/10204/2438Paper presented at the 27th Annual Southern African Transport Conference 7 - 11 July 2008 "Partnership for research and progress in transportation", CSIR International Convention Centre, Pretoria, South AfricaA healthy road transport systems is essential for any country's social and economic development. It is generally observed that if road deterioration is allowed to increase, the economy will need significantly larger expenditures in subsequent years to keep the road maintenance backlog constant. This paper is part of a larger study whose main purpose is to investigate the dynamic behaviour of vehicles on the roads and how the observed behaviour can be effectively combined with other factors measured on the road and driver to assess the integrity of road and vehicle infrastructure. In this paper, vehicle vibration data are applied to an artificial neural network to reconstruct the corresponding road surface profiles. The results show that the technique is capable of reconstructing road profiles within an error margin of 45 percent while with careful control of principal error sources, the technique may achieve 20 percent error margin. This is considered to be reasonable enough for application to condition monitoring of unpaved roads servicing heavy vehiclesenArtificial neural networkRoad condition monitoringRoad profile reconstructionVehicle dynamic modellingVehicle vibrationSATCConference PresentationNgwangwa, H., Heyns, P., Labuschagne, F., & Kululanga, G. (2008). Overview of the neural network based technique for monitoring of road condition via reconstructed road profiles. Southern African Transport Conference (SATC). http://hdl.handle.net/10204/2438Ngwangwa, HM, PS Heyns, FJJ Labuschagne, and GK Kululanga. "Overview of the neural network based technique for monitoring of road condition via reconstructed road profiles." (2008): http://hdl.handle.net/10204/2438Ngwangwa H, Heyns P, Labuschagne F, Kululanga G, Overview of the neural network based technique for monitoring of road condition via reconstructed road profiles; Southern African Transport Conference (SATC); 2008. http://hdl.handle.net/10204/2438 .TY - Conference Presentation AU - Ngwangwa, HM AU - Heyns, PS AU - Labuschagne, FJJ AU - Kululanga, GK AB - A healthy road transport systems is essential for any country's social and economic development. It is generally observed that if road deterioration is allowed to increase, the economy will need significantly larger expenditures in subsequent years to keep the road maintenance backlog constant. This paper is part of a larger study whose main purpose is to investigate the dynamic behaviour of vehicles on the roads and how the observed behaviour can be effectively combined with other factors measured on the road and driver to assess the integrity of road and vehicle infrastructure. In this paper, vehicle vibration data are applied to an artificial neural network to reconstruct the corresponding road surface profiles. The results show that the technique is capable of reconstructing road profiles within an error margin of 45 percent while with careful control of principal error sources, the technique may achieve 20 percent error margin. This is considered to be reasonable enough for application to condition monitoring of unpaved roads servicing heavy vehicles DA - 2008-07 DB - ResearchSpace DP - CSIR KW - Artificial neural network KW - Road condition monitoring KW - Road profile reconstruction KW - Vehicle dynamic modelling KW - Vehicle vibration KW - SATC LK - https://researchspace.csir.co.za PY - 2008 SM - 978-1-920017-34-7 T1 - Overview of the neural network based technique for monitoring of road condition via reconstructed road profiles TI - Overview of the neural network based technique for monitoring of road condition via reconstructed road profiles UR - http://hdl.handle.net/10204/2438 ER -