Multi-Source Monitoring Data Fusion Comprehensive Evaluation Method for the Safety Status of Deep Foundation Pit

Abstract

Construction of the deep foundation pit (DFP) in subway stations is fraught with significant uncertainties, which may cause project delays due to discrepancies between single-indicator monitoring warning information and actual conditions at the site. Therefore, this article proposes a safety assessment method for DFP based on the Game-Cloud Model. An entirely quantitative assessment index system is established with on-site monitoring projects according to the design safety classification of DFP. Considering the one-sidedness of using a single method to determine the weights of assessment indices, game theory is introduced to calibrate the subjective and objective weights determined by the grey decision-making trial and evaluation laboratory (GDEMATEL) and the entropy method, respectively. Next, we use the forward cloud generator of the cloud model (CM) to generate the safety level membership function of the evaluation indicators. Finally, we quantitatively calculate the synthetic safety level of DFP using the comprehensive evaluation approach. A 19-day dynamic assessment was conducted on the actual engineering project by the proposed method. The results indicated that the synthetic safety level of the assessed area ranged between grades Ⅰ and Ⅱ, corresponding to Negligible and Acceptable in the acceptance criteria. Compared with the single-indicator monitoring warning results, it was more in line with on-site observation, which verified its reliability and practicality.