Research on conveyor belt damage detection method based on FDEP-YOLOv8.

ABSTRACT: During the operation of belt conveyors, damage to the conveyor belt (such as tearing, breaking, and scratching) is a major safety hazard. Aiming at the specific challenges of the existing detection methods, such as the difficulty in distinguishing damage from background texture in complex material scenarios, low efficiency of manual inspection, and limited hardware resources, this paper proposes a conveyor belt damage detection algorithm based on the improved YOLOv8. The main improvements include: using the ‌Focal Modulation module‌ to replace the SPPF structure in the backbone network and enhance the feature expression ability; Introduce the ‌ dynamic upsampling module (Dysample) ‌, focus on sampling the target area, and effectively suppress the interference of similar backgrounds; Embed

SUBMITTER: Yuan Y 

PROVIDER: S-EPMC12534561 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature