Detection, Isolation, and Magnitude Estimation of Unknown Flows in Open-Channel Irrigation Systems

The development of modeling and estimation strategies, useful for determining the magnitude and location of unknown flows such as seepage and leaks, appears as a valuable tool to increase the efficiency of the open-channel irrigation systems (OCIS). However, it has been identified that in OCIS, most...

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Detalhes bibliográficos
Autores: Conde, Gregory Johann, Quijano, Nicanor, Ocampo-Martínez, Carlos
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2021
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositório:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/261170
Acesso em linha:http://hdl.handle.net/10261/261170
Access Level:Acceso aberto
Palavra-chave:Unknown flows
Leaks
Seepage
Estimation
Open channels
Irrigation systems
Open canal
Descrição
Resumo:The development of modeling and estimation strategies, useful for determining the magnitude and location of unknown flows such as seepage and leaks, appears as a valuable tool to increase the efficiency of the open-channel irrigation systems (OCIS). However, it has been identified that in OCIS, most of the strategies reported on detection, isolation, and magnitude estimation of unknown flows (DIMEUF) have been developed from linear models that do not include information about energy balances along the channels, where these balances are fundamental to differentiate changes of levels due to conduction effects, from changes of levels due to unknown flows. Therefore, in this work, a recent OCIS modeling approach, which includes mass and energy balances for each channel and non-linear hydraulic descriptions of the flows, is explored in the development of two strategies for DIMEUF based on the moving horizon estimation (MHE) approach. The first strategy is deterministic, designed under the assumption that by filtering of the measurements, the noise can be sufficiently attenuated. Therefore, the noise information is not included in the design process. On the other hand, the second strategy is stochastic, and includes remaining noise information in the design process. The developed strategies have been tested using data from a testbed implemented in a specialized software, and the results show that, in a large operation region, the proposed strategies are capable of accurately describe the channel behavior and unknown flows, and that the inclusion of the remaining noise information increases the performance of the strategies for DIMEUF.