Non-concurrent leak diagnosis in pipelines using an LPV Kalman filter approach

This paper addresses the non-concurrent leak diagnosis problem in pipelines through a discrete-time LPV Kalman filter, considering the availability of pressure head and flow rate measurements at the ends of the pipeline. This method avoids linearization while preserving the nonlinear dynamics of the...

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Detalles Bibliográficos
Autores: Hernández Gómez, Octavio Adrián, Begovich Mendoza, Ofelia, Puig Cayuela, Vicenç|||0000-0002-6364-6429, Delgado Aguiñaga, Jorge Alejandro
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:dnet:upcommonspor::c858086ff908af8e26900ecdab7b5981
Acceso en línea:https://hdl.handle.net/2117/460197
https://dx.doi.org/10.1016/j.ifacol.2025.10.066
Access Level:acceso abierto
Palabra clave:Leak detection
Isolation
LPV systems
Kalman filter
Linear matrix inequalities
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
Descripción
Sumario:This paper addresses the non-concurrent leak diagnosis problem in pipelines through a discrete-time LPV Kalman filter, considering the availability of pressure head and flow rate measurements at the ends of the pipeline. This method avoids linearization while preserving the nonlinear dynamics of the system via an LPV-based representation and the use of the nonlinear embedding approach. Simulations involving two and three leaks demonstrate the accuracy of the method in estimating leak positions and magnitudes.