A parameter identification technique for traffic speed deflectometer tests of pavements

The structural evaluation of existing pavements forms the basis for formulating cost-effective maintenance and rehabilitation strategies. A promising tool for pavement structural evaluation at network level is the Traffic Speed Deflectometer (TSD) test. However, the application of the TSD test is hindered by the lack of a robust and efficient parameter identification technique. To solve this problem, a theoretical model for the TSD test is first formulated. Then, a minimisation algorithm which works best with the theoretical TSD model for parameter identification is selected. Finally, the performance of this combination in processing field TSD measurements is studied. The results show that the modified Levenberg-Marquardt algorithm using all the 9 detection points is most suitable to be combined with the theoretical TSD model for parameter identification, which gives a promising parameter identification technique for TSD tests of pavements. The presented work contributes to the development of technologies for pavement structural evaluation.

Automated summary

This study presents a theoretical model for the Traffic Speed Deflectometer (TSD) test and selects a suitable parameter identification algorithm for this model. The results demonstrate that the modified Levenberg-Marquardt algorithm, when combined with the theoretical TSD model, provides a promising parameter identification technique for TSD tests of pavements.