Design of Pipe-inspection Robot Based on YOLOv3

Author:

Hu Zhangying,Zhou Jingang,Yang Benquan,Chen Aihua

Abstract

Abstract In this paper, a pipe-inspection robot system which uses STM32F103 as control core is designed. The robot system adopts YOLOv3 network model to detect and locate defects of sewage pipeline. The robot uses closed-circuit television system for detection, which is composed of hardware and defect detection. The hardware is mainly composed of robot body, winding coil and upper computer. The motor drive module, body attitude sensor of robot and camera are placed in the pipeline robot. The router, lithium battery and length measurer constitute the winding coil, which is connected with the robot through cable for data transmission and power supply. the upper computer communicates with the cable coil through WIFI, and the staff can send various instructions through the upper computer to control robot operation, and view the status of the pipeline through video. The defect detection of pipeline is mainly realized by YOLOv3 network model, which is used to automatically detect the types of defects in sewage pipeline and mark the location of defects. Finally, the feasibility and effectiveness of defect detection based on YOLOv3 network model are verified by simulation experiments.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference9 articles.

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2. A cascaded deep learning approach for detecting pipeline defects via pretrained YOLOv5 and ViT models based on MFL data;Mechanical Systems and Signal Processing;2024-01

3. A Review on Various in-pipe Inspection Methods for a Pipeline;2023 International Conference on Power, Instrumentation, Control and Computing (PICC);2023-04-19

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