摘要
动车组一级检修是保障动车组列车运行安全的重要周期性维护修程,传统人工一级检修作业需要大量人力投入,其作业效率及质量容易受到人工因素的影响和制约。在广泛深入的现场调研基础上,研究引入基于计算机视觉技术的检修机器人条件下动车组一级检修的生产应用模式和人机协同分工方式,以准确率、识别率等核心指标及人机对比方式跟踪评估动车组检修机器人系统的故障检测能力,对应用检修机器人带来的效率提升和减员效益进行了统计测算,另外运用净现值法综合分析了检修机器人项目投资的经济效益。动车组检修机器人系统目前已可部分替代一级检修人工作业,在保障动车组运行安全的基础上可显著减少作业人员投入并提高作业效率,项目投入将产生明显的经济效益。
The first-level maintenance of Electric Multiple Units(EMUs)is a crucial periodic maintenance program aimed at ensuring the safety of their operations.Traditional manual first-level maintenance operations require significant human resources,and their operational efficiency and quality are susceptible to human factors.Based on extensive and in-depth on-site research,this paper explored the production application mode and human-machine collaborative division of labor under the conditions of first-level maintenance of EMUs using maintenance robots based on computer vision technology.Core indicators such as accuracy,recognition rate,and human-robot comparison were used to track and evaluate the fault detection capability of the EMU maintenance robot system.The study also statistically calculated the efficiency improvement and workforce reduction benefits brought by the application of maintenance robots.Additionally,it conducted a comprehensive economic benefit analysis of the investment in the maintenance robot project using the Net Present Value(NPV)method.The EMU maintenance robot system can now partially replace manual first-level maintenance work,significantly reducing labor input and improving operational efficiency,thereby resulting in substantial economic benefits from the project investment while ensuring the safety of EMU operations.
作者
周喆
ZHOU Zhe(Shanghai EMU Depot,China Railway Shanghai Group Co.,Ltd.,Shanghai 201812,China)
出处
《铁道运输与经济》
北大核心
2024年第1期96-102,共7页
Railway Transport and Economy
关键词
动车组检修
机器人
图像识别
人机协同
净现值法
EMU Maintenance
Robot
Image Recognition
Human-machine Collaboration
NPV Method