A Risk-Cost Analysis for an Increasingly Widespread Monitoring of Railway Lines

Structural Health Monitoring represents an essential tool for detecting timely failures that may cause potential damage to the railway infrastructure, such as extreme weather conditions, natural accidental phenomena, and heavy loads affecting tracks, bridges, and other structures over time. The more thorough the monitoring, the more exact the information can be derived. In this paper, we propose an optimal approach to ensure the maximum railway infrastructure reliability through increasingly widespread and effective monitoring, subject to a budget constraint. More in detail, considered a pre-existing network of zones, each of which is monitored by a set of fixed diagnostic sensors, our goal is to identify new additional areas in which to place the same set of sensors in order to evaluate the geometric and structural quality of the track simultaneously. A kriging technique is used to identify the riskiness of some unsampled locations in order to select the new areas to be monitored. Moreover, two different decision criteria have been introduced, both depending on the risk level of the occurrence of extreme phenomena under investigation and involving the analysis of monitoring and non-monitoring costs. A descriptive analysis of the procedure, which may be used to identify the additional zones to be monitored, is provided in the paper by illustrating the resolution algorithm of the problem. The methodology has been implemented in environment R by using simulated data.