A Dual Factor Analysis System of Talus Slope Stability Based on Post-Processing of Electroencephalography Data

Abstract

Considering the similarity between the physical-mechanical indices of the talus slope and EEG data, this paper attempts to determine the physical-mechanical index distribution and reliability of the talus slope in reference to the post-processing technique of EEG data. Meanwhile, the pure mathematical model was modified to keep the safety factor below the critical value. Specifically, the Kolmogorov–Smirnov (K-S) test and Monte-Carlo (M-C) method, two popular post-processing methods for EEG data were introduced in details. On this basis, the author created a realistic dual index system for stability evaluation of the talus slope. The system was then applied to a case study on a talus slope located on the south of the K13~14 section of Nanhuan Road in Fuxin, a city in Northeast China. Through the analysis of dual index system, the talus slope is determined as generally stable in Case 1, but steps 1, 2 and 3 and the whole slope exhibited signs of sliding due to rainfall infiltration in Case 2. The results agree well with the field data. The research findings shed new light on the studies of slope stability and the handling of complex, nonlinear data.