LAUSR

AbstractA safety monitoring system is usually applied in deep excavations in order to control the construction risk and to ensure the serviceability of adjacent facilities. Considering the mass data collected by different sensors, a reasonable assessment method on the monitoring results is necessary to evaluate the safety state of both the deep excavation itself and the surrounding environment. By introducing the conception of data fusion, a comprehensive assessment method is presented to find the anomaly in the safety monitoring results in this paper. Data fusion analyses on both a single monitoring item and the correlation of multiple monitoring items are proposed and studied. The one-class support vector machines (SVMs) are used to improve the data fusion analysis between a single monitoring item and different excavation parameters, and then developed to three-dimensional (3D) fusion analysis on a single item and multiple parameters of an excavation. The mechanical and geometric patterns between differ...