 In the context of urban rail transit networks, signal interruptions can cause both localized and widespread disruptions. These disruptions can lead to cascading failures across the entire network, making it difficult to manage and operate the system effectively. To address this issue, it is important to monitor the status of individual stations in real time and identify those stations that are experiencing abnormal conditions. This allows for quick identification and resolution of any issues before they become too severe. Additionally, the spacer temporal distribution of the abnormal stations can be analyzed to better understand how the disruption spreads throughout the network. By understanding the propagation law of disruptions, rail management departments will have a better understanding of how to respond quickly and efficiently when disruptions occur. This article was authored by Wenhan Zhou, Tong Feili, Rui Ding, and others.