Abstract
Research findings on Robotics are disc ussed in a new report. According to news reporting originating in Changsha, Peop le's Republic of China, by NewsRx journalists, research stated, "Box girders ser ve as crucial upper-level load-bearing components in high-speed railway simply-s upported bridges, requiring sufficient structural rigidity during operation. The occurrence of cracks compromises the overall stiffness of the structure, posing significant safety risks and potentially leading to substantial loss of life an d property." Funders for this research include National Natural Science Foundation of China ( NSFC), Central South University Research Program of Advanced Interdisciplinary S tudies. The news reporters obtained a quote from the research from the School of Civil E ngineering, "Therefore, it is essential to rapidly and accurately detect cracks within the girder structure, particularly in the interior of box girders where a ccess for maintenance by personnel is inconvenient. To address this issue, this paper proposes a robot-based framework for crack detection in high-speed railway box girder, and accurately evaluate the damage status of structures. This compr ehensive framework includes an image generation network for generating high-qual ity crack images, a lightweight object detection algorithm for rapidly identifyi ng crack targets, and a high-precision semantic segmentation algorithm for accur ately extracting crack pixels. Comparative analysis with mainstream algorithms v alidates the superiority of the proposed methods."
NETL
NSTL