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

A project disaster warning system based on collaborative fusion of multi-physical field monitoring data, comprising:

• a data acquisition and preprocessing module, configured to acquire and preprocess multi-sensor real-time monitoring data of potentially dangerous parts of a project structure to obtain multi-physical field monitoring time sequence data;
• a normalization processing module, configured to perform normalization processing on the multi-physical field monitoring time sequence data to construct a normalized sample matrix;
• a multi-physical field data-level fusion module, configured to analyze sensitivities of various physical field monitoring indicators to a safety state of a project according to the normalized sample matrix, by using a multivariate statistical method;
• a multi-physical field feature-level fusion module, configured to guiding initialization training of a LSTM network according to the sensitivities of various physical field monitoring indicators to the safety state of the project, and obtain output results of the LSTM network through a trained LSTM network;
• a multi-physical field data decision fusion module, configured to obtain 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;
• a disaster danger level evaluation module, configured to determine disaster danger levels of the potentially dangerous parts of the project structure according to the basic probability assignments of various warning levels after fusion, by using a basic probability assignment-based decision method;
• wherein, the project disaster warning system is further configured to give an alarm, based on the determined disaster danger levels of the potentially dangerous parts of the project structure.