Joaquim Blesa

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In this paper, the problem of fault diagnosis of a wind farm is addressed using interval nonlinear parameter varying (NLPV) parity equations. Fault detection is based on the use of parity equations assuming unknown but bounded description of the noise and modeling errors. The fault detection test is based on checking the consistency between the measurements(More)
Inland navigation networks are mainly used for transport with economic and environmental benefits. In a climate change context which leads to the scarcity of the water resource, the control of navigation levels and the supervision of these networks become crucial. Thus, this paper is focused on the sensors Fault Detection and Isolation of inland navigation(More)
This work presents an optimization strategy that maximizes the leak locatability performance of water distribution networks (WDN). The goal is to characterize and determine a sensor configuration that guarantees a maximum degree of locatability while the sensor configuration cost satisfies a budgetary constraint. The method is based on pressure sensitivity(More)
In this paper, robust fault detection is addressed based on evaluating the residual energy that it is compared against worst-case value (threshold) generated considering parametric modelling uncertainty using interval models. The evaluation of the residual/threshold energy can be done either in the time or frequency domain. This paper proposes methods to(More)
This paper presents a new method for leak localization in Water Distribution Networks that uses a model-based approach combined with Bayesian reasoning. Probability density functions in model-based pressure residuals are calibrated off-line for all the possible leak scenarios by using a hydraulic simulator, being leak size uncertainty, demand uncertainty(More)
In this paper, robust fault detection based on adaptive threshold generation of a non-linear system described by means of a linear parameter-varying (LPV) model is addressed. Adaptive threshold is generated using an interval LPV observer that generates a band of predicted outputs taking into account the parameter uncertainties bounded using intervals. An(More)
We present a robust fault diagnosis method for uncertain multiple input–multiple output (MIMO) linear parameter varying (LPV) parity equations. The fault detection methodology is based on checking whether measurements are inside the prediction bounds provided by the uncertain MIMO LPV parity equations. The proposed approach takes into account existing(More)
This article proposes a robust set-membership fault detection method based on the use of polytopes to bound the parameter uncertainty set. The algorithm is able to handle systems with bounded parameter variation between samples. It is shown that consistency checks indicating faults can be performed in a natural manner with a polytope description of the(More)
This paper deals with the problem of nonlinear set-membership identification and fault detection using a Bayesian framework. The paper presents how the setmembership model estimation can be reformulated from a Bayesian viewpoint in order to determine the feasible parameter set and, in a posterior fault detection stage, to check the consistency between the(More)