Predictive Maintenance with PCA Approach for Multi Automated Railroad Crossing System (ARCS) in The Framework of Prognostic and Health Management (PHM) Planning

Abstract

The existence of level crossings between railroads and road vehicles that do not have gates in areas far from crowds, such conditions require gates that are made automatically to avoid accidents. The Automated Railroad Crossing System (ARCS) is an automatically activated railroad crossing gate where train arrival information is obtained through sensors. For one level crossing, there are several electronic devices installed in the automatic railroad crossing system. It is planned that the automatic railroad crossing system will be installed at several level crossings. The problem is how to estimate the time to perform automatic railroad crossing maintenance at several different locations, For this reason, it is necessary to know the estimated remaining useful life (Remaining Useful Life) of the subsystems. The purpose of this research is to find the estimated remaining useful time (RUL) of the subsystem in the automatic railroad crossing system in order to estimate the time to perform maintenance. The process that is carried out to obtain the remaining useful time is through the Prognostic Health Management System development plan, while the analysis of the estimated remaining useful time is carried out using Principle Component Analysis (PCA), the results of this simulation show promising results to determine the estimated value of the remaining useful time. If it can be known the estimated remaining time of the benefit, it is hoped that the maintenance plan for each automatic railroad crossing system can be carried out more efficiently.