Cone Bearing Estimation Utilizing a Hybrid HMM and IFM Smoother Filter Formulation

Abstract

Cone penetration testing (CPT) is a widely used geotechnical engineering in-situ test for mapping soil profiles and assessing soil properties. In CPT, a cone on the end of a series of rods is pushed into the ground at a constant rate and resistance to the cone tip is measured ( q m ). The q m values are utilized to characterize the soil profile. Unfortunately, the measured cone tip resistance is blurred and/or averaged which can result in the distortion of the soil profile characterization and the inability to identify thin layers. This paper outlines a novel and highly effective algorithm for obtaining cone bearing estimates q t from averaged or smoothed q m measurements. This q t optimal filter estimation technique is referred to as the q t HMM-IFM algorithm and it implements a hybrid hidden Markov model and iterative forward modelling technique. The mathematical details of the q t HMM-IFM algorithm are outline d in this paper along with the results from challenging test bed. The test b ed simulations have demonstrated that the q t HMM-IFM algorithm can derive accurate q t values from challenging averaged q m profiles. This allows for greater soil resolution and the identification and quantification of thin layers in a soil profile.