Abstract:The working environment of aeroengine blades is extremely harsh, leading to various types of surface damage. Surface
inspection at the early stages of damage can effectively prevent blade failure and fracture caused by damage propagation. Currently, the
inspection and evaluation of engine blade surface damage heavily rely on manual operation, which not only lacks efficiency but also suffers
from susceptibility to human factors. In order to achieve efficient and accurate inspection of engine blade surface damage, from the forms of
blade failure, the damage mechanisms under both non-operating and operating conditions are reviewed, with emphasis on methods com?
monly used in blade surface damage inspection, such as eddy current and penetration. Additionally, this paper summarizes machine vision-
based inspection technology while addressing the challenge posed by dataset scarcity and singularity in machine vision applications. It is
believed that collecting extensive datasets and further enhancing evaluation criteria are key directions of future research on engine blade
surface damage inspection systems. |