Robust fault diagnosis of nonlinear systems using interval constraint satisfaction and analytical redundancy relations

In this paper, a robust fault diagnosis problem for nonlinear systems considering both bounded parametric modeling errors and noise is addressed using parity-equation-based analytical redundancy relations (ARR) and interval constraint satisfaction techniques. Fault detection, isolation, and estimation tasks are considered. Moreover, the problem of quantifying the uncertainty in the ARR parameters is also addressed. To illustrate the usefulness of the proposed approach, a case study based on the well-known wind turbine benchmark is used.This work has been supported by WATMAN (Ref. DPI-2009-13744) and SHERECS Projects (DPI-2011-26243) of the Spanish Science and Innovation Ministry and the DGR of Generalitat de Catalunya (SAC group Ref. 2009/SGR/1491).Peer Reviewe

Fault detection and isolation for a wind turbine benchmark using a mixed Bayesian/Set-membership approach

This paper addresses the problem of fault detection and isolation of wind turbines using a mixed Bayesian/Set-membership approach. Modeling errors are assumed to be unknown but bounded, following the set-membership approach. On the other hand, measurement noise is also assumed to be bounded, but following a statistical distribution inside the bounds. To avoid false alarms, the fault detection problem is formulated in a set-membership context. Regarding fault isolation, a new fault isolation scheme that is inspired on the Bayesian fault isolation framework is developed. Faults are isolated by matching the fault detection test results, enhanced by a complementary consistency index that measures the certainty of not being in a fault situation, with the structural information about the faults stored in the theoretical fault signature matrix. The main difference with respect to the classical Bayesian approach is that only models of fault-free behavior are used. Finally, the proposed FDI method is assessed against the wind turbine FDI benchmark proposed in the literature, where a set of realistic fault scenarios in wind turbines are proposed.Peer Reviewe

Robust fault diagnosis of non-linear systems using constraints satisfaction

Presentado al 7th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes celebrado en Barcelona del 30 de junio al 3 de julio de 2009.In this paper, the robust fault diagnosis problem for non-linear systems considering both bounded parametric modeling errors and noises is addressed using constraints satisfaction. Combining available measurements with the model of the monitored system, a set of analytical redundancy relations (ARR), relating only known variables, can be derived. These relations will be used in the fault diagnosis procedure to check the consistency between the observed and the predicted system behaviour. When some inconsistency is detected, the fault isolation mechanism will be activated in order to provide an explanation of the possible cause. Finally, a fault estimation procedure is used to estimate the fault size. To illustrate the usefulness of the proposed approach, a case study based on a well-known four tanks systems control benchmark is used.This work was supported by the project 'Integración de técnicas avanzadas de modelado, control y supervisión aplicadas a la gestión del ciclo integral del agua ' (4797). This work has beensupported by the CICYT Ref. DPI 2006-11944 of the Spanish Science and Technology Ministry, the Juan de la Cierva Research Programme (ref. JCI-2008-2438), and the DGR of Generalitat de Catalunya (SAC group Ref. 2005/SGR/00537).Peer Reviewe

Diseño de tareas persona-robot en el ámbito académico

[ES] Este artículo expone la necesidad de adaptación del currículo universitario a las nuevas tecnologías, en concreto en aspectos de robótica colaborativa. Y se incide cómo, a través de la disciplina interacción persona-ordenador, es posible aportar aspectos de diseño de interacción con la finalidad de mejorar el rendimiento de sistemas persona-robot. La principal contribución de este artículo es el contexto interdisciplinar, que transcurre inicialmente desde la ergonomía e interacción para fusionarse con aspectos de ingeniería y tecnología.[EN] This article exposes the need to adapt the University curriculum to new technologies, in particular collaborative robotics. In addition, this article shows how, through the field of human-computer interaction, it is possible to provide interaction design approach with the purpose of improving the performance of human-robot systems. The main contribution of this article is an interdisciplinary context, which initially goes from ergonomics and interaction to merge with engineering and technology aspectsEl desarrollo de este trabajo ha sido posible con el soporte económico del programa ERDF Operational Program of Catalonia 2014-2020

Robust Fault Diagnosis of Non-linear Systems using Interval Constraint Satisfaction and Analytical Redundancy Relations

In this paper, the robust fault diagnosis problem for non-linear systems considering both bounded parametric modelling errors and noises is addressed using parity equation based Analytical Redundancy Relations and Interval Constraint Satisfaction techniques. Fault detection, isolation and estimation tasks are considered. Moreover, the paper addresses the problem of determining the uncertainty in the parameters of the used uncertain ARRs. To illustrate the usefulness of the proposed approach, a case study based on the well known wind turbine benchmark is used

Leak localization in water distribution networks using pressure residuals and classifiers

Trabajo presentado al 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS) celebrado en Paris (Francia) del 2 al 4 de septiembre de 2015.In order to take into account the scarcity of the water resource and the increasing of the population, the management of drinking water networks has to be improved with the use of new tools and actions that allows fighting against wasting water. The monitoring of drinking water networks is based on the use of sensors to locate malfunctions (leaks, quality/contamination events, etc.). Practical implementation has to be carried out by optimizing the placement of the number of sensors and improving the detection and localization of malfunctions. Techniques for the detection and localization of leaks have been proposed in the last years based on the evaluation of residuals obtained by means of the comparison between the measurements obtained by the sensors and the values obtained by simulating the water network in a leak free scenario. In this paper, a data-driven approach based on the use of statistical classifiers working in the residual space is proposed for leak localization. The classifiers are trained using leak data scenarios in all the nodes of the network considering uncertainty in demand distribution, additive noise in sensors and leak magnitude. Finally, the proposed approach is tested using the well-known Hanoi network benchmark.This work has been partially funded by the Spanish Ministry of Science and Technology through the Project ECOCIS (Ref. DPI2013-48243-C2-1-R) and Project HARCRICS (Ref. DPI2014-58104-R), and by EFFINET grant FP7-ICT-2012-318556 of the European Commission.Peer Reviewe

Fault Tolerant Control Design using the LPV approach

International audienceIn this paper, a Fault Tolerant Control (FTC) design method based on Linear Parameter Varying (LPV) gainschedulingtheory is proposed. The main contribution is the design of a fault-tolerant state-feedbackobserver-based controller based on a polytopic LPV representation where faults are considered in thesame way that those parameters that vary with the operating point.Within this framework, the ranges offault magnitudes that are wanted to be tolerated can be specified as design parameters. Control specificationsare defined in terms of H∞ or H2 performance in combination with regional pole placement, as traditionallydone in conventional LPV control. Passive and active FTC formulations are developed, the latter assumingthe availability of on-line fault estimations. In both cases, the associated controller synthesis methods arebased on the well established LPV-LMI framework. Additionally, a fault estimation procedure is provided toallow the implementation of the active formulation. Finally, the use of the proposed method is illustrated byapplying it to the FTC of a two degree of freedom helicopter

Leak detection and localization in water distribution networks by combining expert knowledge and data-driven models

Leaks represent one of the most relevant faults in water distribution networks (WDN), resulting in severe losses. Despite the growing research interest in critical infrastructure monitoring, most of the solutions present in the literature cannot completely address the specific challenges characterizing WDNs, such as the low spatial resolution of measurements (flow and/or pressure recordings) and the scarcity of annotated data. We present a novel integrated solution that addresses these challenges and successfully detects and localizes leaks in WDNs. In particular, we detect leaks by a sequential monitoring algorithm that analyzes the inlet flow, and then we validate each detection by an ad hoc statistical test. We address leak localization as a classification problem, which we can simplify by a customized clustering scheme that gathers locations of the WDN where, due to the low number of sensors, it is not possible to accurately locate leaks. A relevant advantage of the proposed solution is that it exposes interpretable tuning parameters and can integrate knowledge from domain experts to cope with scarcity of annotated data. Experiments, performed on a real dataset of the Barcelona WDN with both real and simulated leaks, show that the proposed solution can improve the leak detection and localization performance with respect to methods proposed in the literature.This work has been funded by the Spanish Ministry of Economy and Competitiveness (MEINCOP), the Spanish State Research Agency (AEI) and by European Regional Development Fund (ERDF) through project DEOCS (ref. DPI2016-76493-C3-3-R) and through grant IJCI-2014-2081, by the European Commission through contract EFFINET (ref. FP7-ICT2011-8-318556), and by the Catalan Agency for Management of University and Research Grants (AGAUR), the European Social Fund (ESF) and the Secretary of University and Research of the Department of Companies and Knowledge of the Government of Catalonia through the grant FI-DGR 2015 (ref. 2015 FI_B 00591)

Data-driven approach for leak localization in water distribution networks using pressure sensors and spatial interpolation

This paper presents a new data-driven method for leak localization in water distribution networks. The proposed method relies on the use of available pressure measurements in some selected internal network nodes and on the estimation of the pressure at the remaining nodes using Kriging spatial interpolation. Online leak localization is attained by comparing current pressure values with their reference values. Supported by Kriging; this comparison can be performed for all the network nodes, not only for those equipped with pressure sensors. On the one hand, reference pressure values in all nodes are obtained by applying Kriging to measurement data previously recorded under network operation without leaks. On the other hand, current pressure values at all nodes are obtained by applying Kriging to the current measured pressure values. The node that presents the maximum difference (residual) between current and reference pressure values is proposed as a leaky node candidate. Thereafter, a time horizon computation based on Bayesian reasoning is applied to consider the residual time evolution, resulting in an improved leak localization accuracy. As a data-driven approach, the proposed method does not need a hydraulic model; only historical data from normal operation is required. This is an advantage with respect to most data-driven methods that need historical data for the considered leak scenarios. Since, in practice, the obtained leak localization results will strongly depend on the number of available pressure measurements and their location, an optimal sensor placement procedure is also proposed in the paper. Three different case studies illustrate the performance of the proposed methodologies.This work has been funded by the Ministerio de Economía, Industria y Competitividad (MEICOMP) of the Spanish Government and FEDER through the project DEOCS (ref. DPI2016-76493) and SCAV (ref. DPI2017-88403-R), by MEICOMP and FEDER through the grant IJCI-2014-20801, and by the Catalan Agency for Management of University and Research Grants (AGAUR), the European Social Fund (ESF) and the Secretary of University and Research of the Department of Companies and Knowledge of the Government of Catalonia through the grant FI-DGR 2015 (ref. 2015 FI B 00591) and the Advanced Control Systems (SAC) group grant (2017 SGR 482). The second author acknowledges the support from the Serra Húnter program

Incremental upgrading sensor placement methodology: Application to the leak localization in water networks

This paper presents a new methodology for sensor reallocation in large scale-systems considering fault isolation purposes. From an initial set consisting of a limited number of sensors already installed in certain locations of the system, the proposed methodology produces a new sensor placement where some of the sensors are strategically reallocated in different but available places of the system. The procedure is posed as an optimization problem where the performance index is specific of the fault isolation method to be used. The algorithm that solves the problem is an incremental upgrading approach based in the Sequential Forward Floating Search algorithm and it combines a forward phase (where sensors are added sequentially) with a backward phase (where sensors can be individually removed from the original sensor placement). The proposed methodology is illustrated by means of its application to the problem of leak localization in Water Distribution Networks (WDN), where the particular placement of the pressure sensors has a great impact in the ability to isolate the leaky node. Also, since only a limited number of pressure sensors can be installed in some nodes, space interpolation techniques must be used to estimate the pressure in the other network nodes. The performance of the localization process is measured in terms of pipe distance from the estimated leaky node candidate to the real leaky node. The proposed methodology is applied to two District Metered Areas of the WDN of a metropolitan area of Spain, in simulation and using real measurements and leak scenarios.This work has been partially funded by L-BEST Project (PID2020-115905–RB-C21) funded by MCIN/ AEI /10.13039/501100011033, by the European Commission through contract EFFINET (ref. FP7-ICT2011-8-318556), and by the Catalan Agency for Management of University and Research Grants (AGAUR), the European Social Fund (ESF) and the Secretary of University and Research of the Department of Companies and Knowledge of the Government of Catalonia through the grant FI-DGR 2015 (ref. 2015 FI_B 00591)