The invention discloses a
submarine scoured pipeline stability early warning method based on
artificial intelligence, and relates to the technical field of
submarine pipeline protection, and the method comprises the steps: collecting and sorting
submarine pipeline historical reconnaissance data and
monitoring data of a target region; and constructing a
seabed-
submarine pipeline local fine three-dimensional hydrodynamic-
sediment numerical model on the basis of a solution Navier-Stokes equation and a
sediment transportation model. According to the method, the historical reconnaissance data, the
monitoring data and the numerical model result are integrated, the
coupling effect of various factors can be comprehensively considered, then the dynamic characteristics of
seabed scouring are more comprehensively captured, key scouring factors influencing the stability of the pipeline are more accurately recognized, and meanwhile, the scouring process and result simulated by the numerical model are combined, so that the stability of the pipeline is improved. According to the method, the
stress distribution and deformation conditions of the pipeline under different scour depths can be analyzed more accurately, then an early warning
signal is sent out in advance, the risk that the pipeline is damaged due to scour is effectively reduced, and the reliability and accuracy of early warning are improved.