Railways are among the most efficient and widely used mass transportation systems for mid-range distances. To enhance the attractiveness of this type of transport, it is necessary to improve the level of comfort, which is much influenced by the vibration derived from the train motion and wheel-track interaction; thus, railway track infrastructure conditions and maintenance are a major concern. Based on discomfort levels, a methodology capable of detecting railway track infrastructure failures is proposed. During regular passenger service, acceleration and GPS measurements were taken on Alfa Pendular and Intercity trains between Porto (Campanhã) and Lisbon (Oriente) stations. ISO 2631 methodology was used to calculate instantaneous floor discomfort levels. By matching the results for both trains, using GPS coordinates, 12 track section locations were found to require preventive maintenance actions. The methodology was validated by comparing these results with those obtained by the EM 120 track inspection vehicle, for which similar locations were found. The developed system is a complementary condition-based maintenance tool that presents the advantage of being low-cost while not disturbing regular train operations.This research was funded by Fundação para a Ciência e Tecnologia, grant number PD/BD/143161/2019. The authors also acknowledge the financial support from the Base Funding-UIDB/04708/2020 and Programmatic Funding-UIDP/04708/2020 of the CONSTRUCT—Instituto de Estruturas e Construções, funded by national funds through the FCT/MCTES (PIDDAC).This work is a result of the project “FERROVIA 4.0”, reference POCI-01-0247-FEDER- 046111, co-funded by the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020) and the Lisbon Regional Operational Programme (LISBOA 2020) under the PORTUGAL 2020 Partnership Agreement. The first author thanks Fundação para a Ciência e Tecnologia (FCT) for a PhD scholarship under the project iRail (PD/BD/143161/2019). The authors would like to acknowledge the support of the projects FCT LAETA–UIDB/50022/2020, UIDP/50022/2020, and UIDB/04077/2020. No potential competing interest was reported by the authors
