The invention discloses a structure safety assessment method and
system based on a
robot holder image, and relates to the field of structure safety assessment. The method comprises the following steps: S1, controlling a
robot carrying a holder and a multi-
modal sensor group to collect a surface image, internal
heat distribution and three-dimensional contour data of a target structure, constructing a model based on an improved
deep learning network to identify and classify surface defects and internal hidden damages, quantifying the defects through an
algorithm, and outputting the data; s2, constructing a digital twin based on the three-dimensional contour data, mapping design parameters, tracking a
dynamic feature point displacement trajectory to calculate deformation parameters, and outputting a deformation
damage analysis result through a correlation model; and S3, calling a pre-constructed
reinforcement learning adaptive evaluation model, inputting defect quantitative data and a deformation
damage analysis result, and outputting a safety level and a
risk evaluation result combined with a preset specification. The method improves the evaluation precision and efficiency, and adapts to the evaluation requirements of different target structures.