Wear assessment employing remote condition monitoring: a case study

摘要: Abstract Over the past few years, there have been many advances in rail-based transport, i.e. higher speeds, increasing numbers of longer trains, shorter intervals between greater axle loads, etc. Individually and together, these factors are resulting need for standards track quality associated infrastructure components. At same time, railway undertakings to minimise expenditure on providing redundancy cope with exceptional circumstances. Therefore, most important performance characteristics required reliability reduced maintenance cost, while consolidating safety improvements. Turnouts amongst last remaining “fail hard” elements system exposed severe environmental influences. There now situations where failure an individual turnout or a single switch rail can cause total shutdown potentially very large losses, terms service reliability, operational schedules financial consequences. Preventing such problems is therefore reliable passenger freight service. Wear one affecting turnouts. Consequently, wear control method required. assessment mechanisms components often require remote monitoring equipment condition, involving sensing states, transmission data collected analysis signals. In any real environment, signals measurements condition systems suffer from distortion electrical noise. To be viable, also robust algorithms detect faults. Noise could indicate problems, none exist reality. preparing this paper, teams at Universities Sheffield (UK) Castilla-La Mancha (Spain) studied application (RCM) used turnouts their operation. The authors put forward algorithm monitor related propose Kalman filter linear discrete data-filtering problem.