Abstract
Rotating mechanical components are critical elements in the rail industry. A healthy condition of these mechanisms is vital to provide a reliable long-term service. In this regard, optimising the corresponding maintenance operations with predictive technology offers many attractive advantages to operating and maintenance companies, being the security and the LLC (life cycle cost) improvement (economic savings) some of the most important criteria. To this end, this paper describes the ongoing research and development works for Prognosis and Health Management at ALSTOM Transport, named Condition Based Maintenance On Board (CBM OB). The system is coined CBM OB after its purpose to be of flexible and easy use and installation on moving train units. It describes a general-purpose framework, with an emphasis on data processing power. It is based on a Wireless Sensor Network that is able to monitor, diagnose and prognosticate the health condition of different mechanical elements. The architecture of this framework is modular by design in order to accommodate data processing modules fitting specific needs, adapted to the peculiarities of the problem under analysis and to the environmental conditions of the data acquisition. Empirical experimentation shows that CBM OB provides a detailed analysis that is equivalent to other commercial solutions even with stronger hardware equipment.