FAO系统中基于视频和激光雷达的异物检测融合算法研究

2022 5th International Conference on Renewable Energy and Power Engineering (REPE) Pub Date : 2022-09-28 DOI:10.1109/REPE55559.2022.9949511

Qingguang Yu, Shih-Chi Wang, Youqi Liu, Lintao Zhang, Ashton Yuxuan Tan, Chengbo Siow, Yujin Wang, Guanzi Cai

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引用次数: 1

摘要

本文旨在研究地铁屏蔽门的融合算法，使未来的全自动操作系统更安全、更高效。本文采用视频与光探测与测距(LIDAR)融合算法技术，提出了一种基于视频图像识别和雷达点云融合的双准则人工智能(AI)策略，用于地铁站台门间隙异物检测。创新性地提出了一种传感器交叉叠加分层安装的新方法，实现了对间隙异物的冗余检测功能。交叉检测提高了检测装置的可靠性，而采用二维传感器实现三维检测效果。开发的系统为地铁信号系统提供安全联锁信号，将报警信息传递给综合监控系统，再将智能手环报警信息推送给现场操作人员。

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Research of a Foreign Objects Detection Fusion Algorithm Using Video and LIDAR in FAO System

This paper aims to research a fusion algorithm for subway screen doors to make future fully automatic operation (FAO) systems safer and more efficient. This paper adopts video with light detection and ranging (LIDAR) fusion algorithm technology, and proposes a dual-criteria artificial intelligence (AI) strategy using video image recognition and radar point cloud fusion to detect foreign objects in the gap between subway platform doors. A novel approach of cross-stacking and layered installation of sensors is innovatively proposed to realize the function of redundant detection of foreign objects in the gap. Cross-checking improves the reliability of the detection device while 2D sensors are used to achieve 3D detection effects. The developed system provides safety interlocking signals for the subway signal system, delivering alarm information to the integrated monitoring system, then pushes the smart hand ring alarm information to the on-site operators.

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来源期刊

2022 5th International Conference on Renewable Energy and Power Engineering (REPE)

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