随着地铁建设的高速发展，特别是无人驾驶模式运营的推广，预防维修、事后维修、全面生产维修等模式已不再符合智慧地铁高可靠性和安全性的发展趋势。因此，针对郑州地铁的现场运营情况以及日常运维过程中遇到的故障难以及时察觉、故障造成车辆延误等痛点问题，提出了一种基于大数据分析下多参量融合预测评价的智能运维系统。以郑州地铁实际运营情况为例，研发了智能运维系统工程样机，并进行了设备健康状态的可视化评价。

With the rapid developments in subway construction, the promotion of unmanned mode operation, preventive maintenance, post-maintenance, and comprehensive production maintenance are no longer in line with the development trends concerning high reliability and safety of smart subways. Therefore, this study proposes a smart operation and maintenance system based on multi-parameter fusion prediction and evaluation. This system is based on big data analysis according to the on-site operation situation of the Zhengzhou Metro, difficulty of timely detection of faults encountered in daily operation and maintenance, and vehicle delays caused by faults. Using the Zhengzhou Metro as an example, an intelligent operation and maintenance system engineering prototype was established, and a visual evaluation of the equipment health status was conducted.

U231