ABSTRACT
Cone penetration testing (CPT) is an important and widely used geotechnical in-situ test for assessing soil properties and mapping soil profiles. CPT consists of pushing at a constant rate an electronic cone into penetrable soils and recording the resistance to the cone tip or cone bearing (qm ). These values (after correction for the pore water pressure to get qt ) are utilized to characterize the soil profile along with measured sleeve friction and pore pressure. The qm measurements can have significant fluctuations when penetrating sandy, silty gravelly soils, resulting in “high” peaks due to interbedded gravels and stones and “low” peaks due to softer materials or local pore pressure build-up. Furthermore, the qm values are blurred and/or averaged which results in the inability to identify thin layers and the distortion of the soil profile characterization. Baziw Consulting Engineers has invested considerable resources in addressing these two qm measurement challenges. The qmKF algorithm was developed to address the additive measurement noise. In this case the dynamics of qm are modeled within a state-space mathematical formulation and a Kalman filter is then utilized to obtain optimal estimates of qm . The qmHMM algorithm implements a hidden Markov model smoother so that true cone bearing are obtained from the averaged/blurred qm values. This paper outlines the integration of the qmKF and qmHMM algorithms and demonstrates the performance first with test bed simulations (to show the functionality of the algorithm) and then through the analysis of various actual qm data sets.
