Two Applications of Wavelet Analysis for Project Level Pavement Management

Two Applications of Wavelet Analysis for Project Level Pavement Management

R. Hassan

Faculty of Science, Engineering and Technology, Centre for Sustainable Infrastructure, Swinburne University of Technology, Australia

Page: 
217-228
|
DOI: 
https://doi.org/10.2495/SDP-V10-N2-217-228
Received: 
N/A
| |
Accepted: 
N/A
| | Citation

OPEN ACCESS

Abstract: 

Wavelet analysis is a signal processing technique that can be used to decompose longitudinal road surface profile signal into a number of wavebands. The outputs of the analysis include the signals (elevation vs. distance) and energies (a measure of elevation variation, i.e. surface roughness) in the different wavebands. The application of wavelet analysis in road pavement management at project level is described herein through two case studies. The first involves using wavelet analysis outputs in identifying and locating excitation sources of dynamic wheel loads (DWL) along a road section. The second case study involves using these outputs in assessing the effectiveness of rehabilitation treatment in reducing surface roughness in the different wavebands along the length of a road section. The outcomes of this research study indicate that the proposed applications are effective in addressing the intended purposes. Study findings also indicate that using HATI to highlight sections subject to high DWL at network level is promising. However, further testing is required to confirm its suitability at different speeds and operating environments.

These assessment approaches help asset managers to identify and locate surface characteristics that increase pavement damage, propose suitable treatments and assess the quality of these treatments. In addition to achieving value for money, adopting such approach would ensure their assets’ sustainability, mobility and comfort of all road users, in particular truck drivers. Long wavelength roughness with high contributions to DWL also has a detrimental effect on heavy vehicle ride.

Keywords: 

Dynamic wheel loads, granular overlay, heavy articulated truck index, profile data, road pavements, roughness, simulation, wavelet analysis

  References

[1] Hassan, R. & McManus, K., Sustainable mobility for heavy freight vehicles. International Journal of Sustainable Development and Planning, 5(3), pp. 253–268, 2010. doi: http://dx.doi.org/10.2495/sdp-v5-n3-253-268

[2] Doré, G., Flamand, M. & Pascale, P., Analysis of the wavelength content of the longitudinal profiles for C-LTPP test sections. Canadian Journal of Civil Engineering, 29(1), pp. 50–57, 2002. doi: http://dx.doi.org/10.1139/l01-075

[3] Brown, D., Liu, W. & Henning, T.F.P., Identifying pavement deterioration by enhancing the definition of road roughness, Research Report 430. NZTA, NZ Transport Agency Wellington, 2010.

[4] Delanne, Y. & Pereira, P.A.A., Advantages and limits of different road roughness profile signal-processing procedures applied in Europe. Transportation Research Record, 1764, pp. 254–259, 2001. doi: http://dx.doi.org/10.3141/1764-26

[5] Liu,W. & Fwa, T.F., Application of wavelet transform analysis for pavement roughness studies. Proceedings of the Eighth International Conference on Applications of Advanced Technologies in Transportation Engineering, Beijing, pp. 455–459, 2004. doi: http://dx.doi.org/10.1061/40730(144)85

[6] Papagiannakis, A.T., Zelelew, H.M. & Muhunthan, B., A wavelet interpretation of vehiclepavement interaction. International Journal of Pavement Engineering, 8(3), pp. 245–252, 2007. doi: http://dx.doi.org/10.1080/10298430701309378

[7] Wasilewski, F., Wavelet Broswer by Pywavelets, available at http://wavelets.pybytes.com/, 2011 (accessed July 2013).

[8] Sweatman, P.F., A study of the dynamic wheel forces in axle group suspensions of heavy vehicles, ARRB Special Report No. 27, Melbourne, Australia, 1983.

[9] Cebon, D., Handbook of Vehicle Road Interaction, Swets & Zeitlinger Publishers: London, 1999.

[10] OECD, Dynamic Interaction of Vehicle and Infrastructure Experiment (OECD IR6 Project: Dynamic Interaction of Heavy Vehicles with Roads and Bridges, DIVINE Project). Proceedings of the Asia-Pacific Concluding Conference, Melbourne, Australia, 1997.

[11] De Pont, J., Road Profile Characterisation, Transit New Zealand Research Report No. 29, 1994.

[12] Papagiannakis, A.T. & Gujarathi, M.S., Roughness Model Describing Heavy Vehicle-Pavement Interaction, Transportation Research Record 1501, pp. 50–59, 1995.

[13] Cole, D.J. & Cebon, D., Influence of tractor–trailer interaction on assessment of road damaging performance. Proceedings of the Institution of Mechanical Engineers, Part D, Journal of Automobile Engineering, 212, p. 1, 1998. doi: http://dx.doi.org/10.1243/0954407981525759

[14] Bernard, J. & Dolcemascolo, V., Dynamic interaction between instrumented vehicles and pavements. Fifth International Symposium on Heavy Vehicle Weights and Dimensions, Australia, 1998.

[15] Proval, http://www.roadprofile.com/

[16] Evans, R. & Arulrajah A., A new method for aligning and synchronising road profile data for better road roughness growth analysis. 8th International Conference on Managing Pavement Assets, CD-ROM, Paper ICMPA011, 15–19 November, Santiago, Chile, 2011.