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Identification of a fault zone ahead of the tunnel excavation face using the extended Kalman filter
Institution:1. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;2. State Key Laboratory of Disaster Prevention and Mitigation of Explosion and Impact, PLA University of Science and Technology, Nanjing 210014, China;1. School of the Earth Sciences & Resources, China University of Geosciences, Beijing, China;2. Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China;1. Geotechnical and Structural Engineering Research Center, Shandong University, Jinan 250061, China;2. Qingdao Metro Co. Ltd., Qingdao 266000, China
Abstract:Simulation of mechanized tunneling and on-site excavation require very good knowledge of the geomechanical and material properties. Identification of the material must be fast and continuously performed during tunnel excavation for the best possible strategies for advancing the tunnel boring machine. We present in this work the use of the extended Kalman filter (EKF) for identification of the inclined fault zone ahead of the face. The EKF showed fast and stable convergence of the model parameters under study. In comparison with the particle swarm optimization technique applied to the same back analysis problem, faster convergence of the identified parameters as well as high robustness with respect to the choice of the initial parameter values have been observed.
Keywords:Extended Kalman filter  Parameter identification  Fault zone  Back analysis  Tunnel excavation
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