深度学习技术在列车故障自动巡检中的应用
Application of Deep Learning Technology in Automatic Train Fault Inspection
彭辉 1张群慧 1杨灿1
作者信息
- 1. 湖南科技职业学院,湖南长沙 410004
- 折叠
摘要
随着人工智能技术的快速发展,利用人工智能新技术对列车故障进行检测成为当下地铁车辆检修工作的新手段.探讨使用深度学习技术对列车设备进行故障自动诊断的方法,以减少人工检修成本、提高检修效率,同时介绍了全连接神经网络、卷积神经网络、目标检测技术在列车巡检机器人故障自动检测中的应用.
Abstract
With the rapid development of artificial intelligence technology,using new artificial intelligence technologies to detect train faults has become a new method for subway vehicle maintenance work. The article explores the method of using deep learning technology for automatic fault diagnosis of train equipment so as to reduce manual maintenance costs and improve maintenance efficiency. The article also introduces the application of full connect neural network,convolutional neural network and object detection technology in automatic fault detection of train inspection robots.
关键词
深度学习/巡检机器人/故障检测Key words
deep learning/inspection robot/fault detection引用本文复制引用
基金项目
2022年湖南省教育厅科学研究项目(22C0977)
出版年
2024
NETL
NSTL
万方数据