Abstract:The extended Kalman filter method is presented for parameters identification of rock rheological model considering the uncertainty of data due to the complexity of rock material and different observation conditions of laboratory or in-situ experiments. In this method the rheological mechanical parameters are improved iteratively as the state vector of a random process. The Kalman filter function is formulated to perform parameter identification. The method is applied to a kind of clayey soft rock from Goupitan Hydropower Station. Parameters of the generalized Kelvin model are estimated based on the results obtained from uniaxial compression creep tests. The estimated results show the good precision of the extended Kalman filter method. The influence of measuring errors is also discussed. Numerical experiments are carried out to verify the greatly antinoise capability of the current method. It provides an efficient theoretical tool for solving the uncertainty effects in the identification of rock mechanical parameters.