dc.contributor.author | García Márquez, Fausto Pedro | |
dc.contributor.author | Pedregal Tercero, Diego José | |
dc.date.accessioned | 2017-05-15T08:50:26Z | |
dc.date.available | 2017-05-15T08:50:26Z | |
dc.date.issued | 2011-04-11 | |
dc.identifier.citation | Digital Filters | es_ES |
dc.identifier.isbn | 978-953-307-190-9 | |
dc.identifier.uri | http://hdl.handle.net/10578/14131 | |
dc.description.abstract | Faults in mechanisms must be detected quickly and reliably in order to avoid important losses. Detection systems should be developed to minimize maintenance costs and are generally based on consistent models, but as simple as possible. Also, the models for detecting faults must adapt to external and internal conditions to the mechanism. The present chapter deals with three particular maintenance algorithms for turnouts in railway infrastructure by means of discrete filters that comply with these general objectives. All of
them have the virtue of being developed within a well-known and common framework, namely the State Space with the help of the Kalman Filter (KF) and/or complementary Fixed Interval Smoother (FIS) algorithms. The algorithms are tested on real applications and thorough results are shown. | es_ES |
dc.format | application/pdf | es_ES |
dc.language.iso | en | es_ES |
dc.publisher | InTech | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | Maintenance management | es_ES |
dc.subject | Digital Filters | es_ES |
dc.title | Digital Filters for Maintenance Management | es_ES |
dc.type | info:eu-repo/semantics/bookPart | es_ES |
dc.identifier.DOI | 10.5772/15999 | |