Visual Collaborative Maintenance Method for Urban Rail Vehicle Bogie Based on Operation State Prediction

• 作者: Dehong Chen Guili Huang Lin Li Qi Chang Qinghai Gan Yi Liu
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 工学
• 关键词: Rail traffic equipment State prediction Intelligent operation and maintenance 3D visualization
• 年，卷（期）: 2020,（2）
• 页码范围: 237-245
• 页数: 9页
• 分类号: TP3

摘要

The bogie is a crucial component of urban rail vehicles,and its performance plays a decisive role in the safe operation of vehicles.Aiming at the intelligent operation and maintenance requirements of rail transit equipment,in this paper,it takes several key parts of the urban rail vehicle bogie system as research objects,such as motor bearings,frames,fasteners,etc.,and proposes a three-dimensional(3D)visual collaborative maintenance method.Firstly,a multi-sensor urban rail vehicle bogie running simulation experiment analysis platform was constructed,thereby establishing a database of running state and performance characteristics of the bogie in the whole life cycle.Then,the health status of key components of bogie was predicted by the state interval prediction model.Finally,the three-dimensional visual collaborative maintenance model proposed in this paper was integrated to realize the early warning of the bogie operation faults,3D precise guidance of automatic location and maintenance operation information,and collaborative sharing of visual information among multiple users.