Escalator

As one of the key passenger-carrying facilities in subway systems, ensuring the operational safety of escalators is equivalent to ensuring public safety. By adding sensors to key components to collect status data—and combining real-time monitoring data on the escalators’ operational and fault conditions with existing large-scale fault data—Ronds uses PHM (Prognostics and Health Management) theory, IoT technology, and deep learning algorithms to study fault warning trends and establish an escalator fault diagnosis and intelligent early warning system. This transforms “scheduled maintenance” into “condition-based maintenance,” ultimately reducing accidents and lowering total lifecycle maintenance costs for escalators.