Recent developments in prognostic models have led to increased use of prognostic
information to improve the benefits of condition-based maintenance (CBM). Existing CBM …

The railway sector has witnessed a significant surge in condition-based maintenance,
thanks to the proliferation of sensing technologies and data-driven methodologies, such as …

Abstract Multi-Criteria Decision-Making (MCDM) problems necessitate a methodology that is
able to produce reliable and defendable decisions. This is especially the case when it …

Wear of wheel profiles is a common degradation process that significantly impacts the
reliability of wheelsets. In this study, a conditional bivariate Gamma process is constructed to …

The accuracy of physics-based wheel wear prediction approaches depends not only on the
vehicle-track dynamics model but more importantly on the wear model. The currently …

Multivariate functional principal component analysis (MFPCA) is a widely used tool for
modeling and prognosis of degradation signals. However, MFPCA usually assumes …

Relative wheel-rail displacement (RWRD) is an important physical quantity that responds to
the hunting stability and running safety of railway vehicles but detecting this physical …

Various sensors implemented in the railway transportation system brings opportunities in
improving its safety and challenges in fault information mining. Extracting effective and …

The core of condition-based maintenance is the accurate evaluation of equipment state. For
various equipment, performance degradation or regression caused by factors, such as …

Predicting track degradation is extremely important due to its beneficial effects on increasing
track safety and scheduling preventive maintenance. Logistic regression and Gradient …