Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/179576
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Sensor fault diagnosis in inland navigation networks based on a grey-box model |
Autor: | Segovia Castillo, Pablo CSIC ORCID; Blesa, Joaquim CSIC ORCID ; Duviella, Eric; Rajaoarisoa, Lala; Nejjari, Fatiha; Puig, Vicenç CSIC ORCID | Palabras clave: | Large-scale systems Inland waterways Fault diagnosis Grey-box model |
Fecha de publicación: | 11-oct-2018 | Editor: | Elsevier | Citación: | IFAC-PapersOnLine 51(24): 742-747 (2018) | Resumen: | Inland navigation networks are equipped with limnimeters to measure and record water level data for the control of water levels and the management of water resources. When faults occur on sensors, corrupted data can be considered as correct, leading to undesirable management actions. Therefore, it is necessary to detect and localize these faults. In this paper, the detection and localization of sensor faults is performed through the analysis of the parameters of a grey-box model, which are obtained from available real data. The parameters are determined with a sliding window, with the exception of the delays, which are considered known a priori. A fault is detected and then localized when there is a change in the value of the parameters. This approach is well suited for constant faults and particularly well adapted for intermittent faults. Data of an inland navigation reach located in the north of France are used to highlight the performance of the proposed approach. | Versión del editor: | https://doi.org/10.1016/j.ifacol.2018.09.658 | URI: | http://hdl.handle.net/10261/179576 | DOI: | 10.1016/j.ifacol.2018.09.658 | ISSN: | 1474-6670 |
Aparece en las colecciones: | (IRII) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
Sensor fault_Segovia.pdf | 1,01 MB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
SCOPUSTM
Citations
2
checked on 27-mar-2024
WEB OF SCIENCETM
Citations
1
checked on 16-feb-2024
Page view(s)
211
checked on 27-mar-2024
Download(s)
136
checked on 27-mar-2024
Google ScholarTM
Check
Altmetric
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.