A dynamic probabilistic modeling of railway switches operating states

The remote monitoring of the railway infrastructure and particularly the switch mechanism is of great interest for railway operators. The problem consists in detecting earlier the presence of defects in order to alert the concerned maintenance service before a breakdown occurs. For this purpose, this paper introduces a new probabilistic-based approach to dynamically modeling the evolution of condition measurements acquired during switch operations. It consists of two steps. The feature extraction from the electrical power consumption signals which aims at summarizing each signal by a low dimensional feature vector. Then, a specific autoregressive model is proposed to model the dynamical behavior of the switch mechanism.