Research on resilience assessment method of train control on-board system

Area of Science:

• Railway Engineering
• System Reliability Engineering
• Control Systems

Background:

• Assessing train control system performance after failures is challenging.
• System failures are time-dependent, impacting operational continuity.
• Reliability is a key indicator for evaluating system resilience.

Purpose of the Study:

• To propose a novel resilience assessment methodology for train control on-board systems.
• To quantify system performance and resilience after failure recovery.
• To provide insights for intelligent maintenance in high-speed rail.

Main Methods:

• Utilized Discrete Time Bayesian Networks for time-dependent reliability analysis.
• Employed an exponential recovery model to define the performance curve during recovery.
• Applied the resilient triangle area method to quantify resilience size.

Main Results:

• The proposed methodology quantifies system resilience post-failure.
• Cold standby and hot standby designs for the CTCS3-300T system showed resilience of 89.44% and 87.34%, respectively.
• A slight decrease in system performance after failure recovery was observed.

Conclusions:

• The resilience assessment methodology effectively measures post-failure performance.
• Findings indicate a need for operational plan adjustments to mitigate network impact.
• The methodology offers a theoretical basis for intelligent maintenance of high-speed train control systems.