Research

Currently, Yue investigates how SHM and CBM can be combined to realize their capabilities in an effort to improve the performance of rail infrastructure while making these systems more reliable and cost efficient. This will result in a decision-making support tool that connects the SHM techniques to the maintenance management of railway assets. She will integrate prognostic algorithms and decision making based on the resulting remaining useful life or other performance indicators depending on the specific context. 

This PhD research is building on her master thesis research. In her master thesis research Yue investigated asset degradation and maintenance strategies which were found to be the driving factors causing variation in life cycle cost (LCC) of rail infrastructure assets. Yue’s master thesis research proposes a reliability-based LCC model for embedded rail level crossing. This model incorporates uncertainty associated with rail degradation and maintenance interventions, and optimizes the cost effective maintenance strategies from a life cycle perspective.