condition monitoring and supervision of the electric railway 3-phase point machines in railway signalling systems using the state observer

In this paper, an approach is presented to develop a condition monitoring, fault detection, and supervision system to prevent in-service failures of electrical railway 3-phase point machine mechanisms and detect slight changes in the state variables associated with some of the electric parameters of the machines. as a first step, a model of the electric point machine mechanism is discussed. in the following, state observers of the system are described, and techniques for enhanced condition monitoring are reviewed based on an analysis of the simulation of the point machine and a comparison of the data with laboratory and field test measurements. the range of failures of the point machines has been categorized into a set of basic modes. the state observer based on kalman filter analysis allows an analysis of these modes of failure, based on the inputs and its model of system behavior and failures. the proposed method has the advantage of not requiring any equipment beyond a current sensor and the associated processing system.