DAMAGE IDENTIFICATION OF STEAM PIPELINE UNDER HIGH PRESSURE BASED ON NEURAL NETWORK TECHMOLOGY
In nuclear power plants,high-pressure steam pipelines are subjected to many problems,so it is very im-portant to monitor their structural health.In this paper,the scale model of a high-pressure steam pipeline is estab-lished for damage identification by the finite element model updating method and BP neural network.The character-istic parameters of the structure are obtained through the modal acquisition test of the pipeline,and the finite ele-ment model is updated to make it similar to the actual pipeline structure in dynamic response.BP neural network is used to identify the damage condition,and appropriate parameters are selected for training.The results show that the trained neural network has a high accuracy in damage identification.The reliability of the method is verified,provid-ing the reference for the actual damage identification of pipeline structures.
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