New methods for the condition monitoring of level crossings

Level crossings represent a high risk for railway systems. This paper demonstrates the potential to improve maintenancemanagement through the use of intelligent condition monitoring coupled with reliability centred maintenance (RCM). RCMcombines advanced electronics, control, computing and communication technologies to address the multiple objectives ofcost effectiveness, improved quality, reliability and services. RCM collects digital and analogue signals utilising distributedtransducers connected to either point-to-point or digital bus communication links. Assets in many industries use data loggingcapable of providing post-failure diagnostic support, but to date little use has been made of combined qualitative andquantitative fault detection techniques. The research takes the hydraulic railway level crossing barrier (LCB) system as acase study and develops a generic strategy for failure analysis, data acquisition and incipient fault detection. For each barrierthe hydraulic characteristics, the motor’s current and voltage, hydraulic pressure and the barrier’s position are acquired. Inorder to acquire the data at a central point efficiently, without errors, a distributed single-cable Fieldbus is utilised. Thisallows the connection of all sensors through the project’s proprietary communication nodes to a high-speed bus. The systemdeveloped in this paper for the condition monitoring described above detects faults by means of comparing what can beconsidered a ‘normal’ or ‘expected’ shape of a signal with respect to the actual shape observed as new data become available.ARIMA (autoregressive integrated moving average) models were employed for detecting faults. The statistical tests knownas Jarque–Bera and Ljung–Box have been considered for testing the model