Project disaster warning method and system based on collaborative fusion of multi-physics monitoring data

Abstract

A project disaster warning method and system based on collaborative fusion of multi-physical field monitoring data is provided. The method includes: acquiring and preprocessing multi-sensor real-time monitoring data of potentially dangerous parts of a project structure; normalizing multi-physical field monitoring time sequence data to construct a normalized sample matrix; analyzing sensitivities of various physical field monitoring indicators to a safety state of a project by using a multivariate statistical method; guiding initialization training of a LSTM network according to the sensitivities, and obtaining output results of the LSTM network; obtaining basic probability assignments of various warning levels after fusion according to an improved D-S evidence theory based on Chebyshev distance, with the output results of the LSTM network as evidence inputs; determining disaster danger levels of the potentially dangerous parts of the project structure using a basic probability assignment-based decision method.