Integration Techniques of Fault Detection and Isolation Using Interval Observers

An interval observer has been illustrated to be a suitable approach to detect and isolate faults affecting complex dynamical industrial systems. Concerning fault detection, interval observation is an appropriate passive robust strategy to generate an adaptive threshold to be used in residual evaluation when model uncertainty is located in parameters (interval model). In such approach, the observer gain is a key parameter since it determines the time evolution of the residual sensitivity to a fault and the minimum detectable fault. This thesis illustrates that the whole fault detection process is ruled by the dynamics of the fault residual sensitivity functions and by the time evolution of the adaptive threshold related to the interval observer. Besides, it must be taken into account that these two observer fault detection properties depend on the used observer gain. As a consequence, the observer gain becomes a tuning parameter which allows enhancing the observer fault detection performance while avoiding some drawbacks related to the analytical models, as the wrapping effect. In this thesis, the effect of the observer gain on fault detection and how this parameter can avoid some observer drawbacks (i.e. wrapping effect) are deeply analyzed. One of the results of this analysis is the determination of the minimum detectable fault function related to a given fault type. This function allows introducing a fault classification according to the fault detectability time evolution: permanently (strongly) detected, non-permanently (weakly) detected or just non-detected. In this fault detection part of this thesis, two examples have been used to illustrate the derived results: a mineral grinding-classification process and an industrial servo actuator. Concerning the interface between fault detection and fault isolation, this thesis shows that both modules can not be considered separately since the fault detection process has an important influence on the fault isolation result. This influence is not only due to the time evolution of the fault signals generated by the fault detection module but also to the fact that the fault residual sensitivity functions determines the faults which are affecting a given fault signal and the dynamics of this fault signal for each fault. This thesis illustrates this point suggesting that the interface between fault detection and fault isolation must consider a set of fault signals properties: binary property, sign property, fault residual sensitivity property, occurrence order property and occurrence time instant property. Moreover, as a result of the influence of the observer gain on the fault detection stage and on the fault residual sensitivity functions, this thesis demonstrates that the observer gain has also a key role in the fault isolation module which might allow enhancing its performance when this parameter is tuned properly (i.e. fault distinguishability may be increased). As a last point, this thesis analyzes the timed discrete-event nature of the fault signals generated by the fault detection module. As a consequence, it suggests using timed discrete-event models to model the fault isolation module. This thesis illustrates that this kind of models allow enhancing the fault isolation result. Moreover, as the monitored system is modelled using an interval observer, this thesis shows as this qualitative fault isolation model can be built up on the grounds of this system analytical model. Finally, the proposed fault isolation method is applied to detect and isolate faults of the Barcelona’s urban sewer system limnimeters. Keywords: Fault Detection, Fault Diagnosis, Robustness, Observers, Intervals, Discrete-event Systems.En la presente tesis se demuestra que el uso de observadores intervalares para detectar y aislar fallos en sistemas dinámicos complejos constituye una estrategia apropiada. En la etapa de detección del fallo, dicha estrategia permite determinar el umbral adaptativo usado en la evaluación del residuo (robustez pasiva). Dicha metodología, responde a la consideración de modelos con parámetros inciertos (modelos intervalares). En dicho enfoque, la ganancia del observador es un parámetro clave que permite determinar la evolución temporal de la sensibilidad del residuo a un fallo y el mínimo fallo detectable para un tipo de fallo determinado. Esta tesis establece que todo el proceso de detección de fallos viene determinado por la dinámica de las funciones sensibilidad del residuo a los diferentes fallos considerados y por la evolución temporal del umbral adaptativo asociado al observador intervalar. Además, se debe tener en cuenta que estas dos propiedades del observador respecto la detección de fallos dependen de la ganancia del observador. En consecuencia, la ganancia del observador se convierte en el parámetro de diseño que permite mejorar las prestaciones de dicho modelo respecto la detección de fallos mientras que permite evitar algunos defectos asociados al uso de modelos intervalares, como el efecto wrapping. Uno de los resultados obtenidos es la determinación de la función fallo mínimo detectable para un tipo de fallo dado. Esta función permite introducir una clasificación de los fallos en función de la evolución temporal de su detectabilidad: fallos permanentemente detectados, fallos no permanentemente detectados y fallos no detectados. En la primera parte de la tesis centrada en la detección de fallos se utilizan dos ejemplos para ilustrar los resultados obtenidos: un proceso de trituración y separación de minerales y un servoactuador industrial. Respecto a la interfaz entre la etapa de detección de fallos y el proceso de aislamiento, esta tesis muestra que ambos módulos no pueden considerarse separadamente dado que el proceso de detección tiene una importante influencia en el resultado de la etapa de aislamiento. Esta influencia no es debida sólo a la evolución temporal de las señales de fallo generados por el módulo de detección sino también porque las funciones sensibilidad del residuo a los diferentes posibles fallos determinan los fallos que afectan a un determinado señal de fallo y la dinámica de éste para cada uno de los fallos. Esta tesis ilustra este punto sugiriendo que el interfaz entre detección y aislamiento del fallo debe considerar un conjunto de propiedades de dichos señales: propiedad binaria, propiedad del signo, propiedad de la sensibilidad del residuo a un fallo dado, propiedad del orden de aparición de las señales causados por los fallos y la propiedad del tiempo de aparición de estos. Además, como resultado de la influencia de la ganancia del observador en la etapa de detección y en las funciones sensibilidad asociadas a los residuos, esta tesis ilustra que la ganancia del observador tiene también un papel crucial en el módulo de aislamiento, el cual podría permitir mejorar el comportamiento de dicho módulo diseñando éste parámetro del observador de forma adecuada (Ej. Incrementar la distinción de los fallos para su mejor aislamiento). Como último punto, esta tesis analiza la naturaleza temporal de eventos discretos asociada a las señales de fallo generados por el módulo de detección. A consecuencia, se sugiere usar modelos de eventos discretos temporales para modelizar el módulo de aislamiento del fallo. Esta tesis muestra que este tipo de modelos permite mejorar el resultado de aislamiento del fallo. Además, dado que el sistema monitorizado es modelado usando un observador intervalar, esta tesis muestra como este modelo cualitativo de aislamiento puede ser construido usando dicho modelo analítico del sistema. Finalmente, el método propuesto de aislamiento del fallo es aplicado para detectar y aislar fallos en los limnimetros del sistema de alcantarillado de Barcelona. Palabras clave: Detección de Fallos, Diagnosis de Fallos, Robusteza, Observadores, Intervalos, Sistemas de Eventos Discretos

Approximating fault detection linear interval observers using -order interval predictors

"This is the peer reviewed version of the following article:Meseguer, J., Puig, V., and Escobet, T. (2017) Approximating fault detection linear interval observers using ¿-order interval predictors. Int. J. Adapt. Control Signal Process., 31: 1040–1060., which has been published in final form at https://doi.org/10.1002/acs.2746. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."Interval observers can be described by an autoregressive-moving-average model while ¿-order interval predictors by a moving-average model. Because an autoregressive-moving-average (ARMA) model can be approximated by a moving-average model, this allows establishing the equivalence between interval observers and interval predictors. This paper deals with the fault detection application and focuses on the equivalence between the ¿-orderintervalpredictorsand the interval observers from the point of view of the fault detection performance. The paper also proves that it is possible to obtain an equivalent ¿ - order interval predictor for a given interval observer with the same fault detection properties by the appropriate selection of the ¿ - order. A condition for selecting the minimal order that provides the ¿ - order interval predictor equivalent to a given interval observer is derived. Moreover, because the wrapping effect could be avoided by tuning properly the interval observer, we can find an equivalent ¿ - order interval predictor such that it also avoids the wrapping effect. Finally, an example based on an industrial servo actuator will be used to illustrate the derived results. Copyright © 2016 John Wiley & Sons, Ltd.Peer ReviewedPostprint (author's final draft

Advanced integrated real-time control of combined Urban drainage systems using MPC

Combined urban drainage system (CUDS) collect both wastewater and raining water through sewer networks to wastewater treatment plants (WWTP) before releasing to the environment. During storm weather, rain and wastewater can overload the capacity of the CUDS and/or the WWTPs, producing combined sewer overflows (CSO). In order to improve the management efficiency of CUDS, advanced real-time control (RTC) of detention and diversion infrastructures in the sewer systems has been proven to contribute to reducing the CSO volumes. This work considers the integrated RTC of sewer network and WWTPs based on model predictive control (MPC) and taking into account the water quality as well as quantity, with the objective of minimizing the environmental impact of CSO on receiving waters. The control approach is validated using a real pilot Badalona sewer network in Spain. The first results, discussion and conclusions are also provided.Peer ReviewedPostprint (author's final draft

Model calibration for leak localization, a real application

The localization of leaks in Water Distribution Networks has a major relevance in terms of environmental and economic efficiency. This localization is generally carried on in situ by human operators using time consuming methods like acoustic loggers. Nevertheless, the automated aid provided to the operators is continuously increasing thanks to the exhaustive use of models. Models that have to be calibrated and updated in order to provide proper help and an improvement in the leak search. This paper presents an experience of leak localization using steady state models combined with a demand calibration algorithm. The calibration produces a notable improvement of the localization accuracy and signals changes in the network configuration. Results presented are based on real data and a real leak provoked for the test.Peer ReviewedPostprint (published version

Fault-tolerant model predictive control applied to integrated urban drainage and sanitation systems for environmental protection

This paper presents a FTC framework for a Real-Time MPC-based Controller applied to Integrated Urban Drainage and Sanitation Systems (UDSSs) which was proposed in the LIFE EFFIDRAIN project. This project deals with the pollution of surface waters due to CSOs and overflows from UDSSs during wet weather. The main purpose of the proposed FTC framework is to preserve as much as possible, the performance of the MPC-based Controller in terms of operation objectives when anomalies affecting the integrated ICT elements (sensors and actuators) occurs. The performance of the FTC controller has been tested using a realistic case of study.Peer ReviewedPostprint (author's final draft

Pumps condition assessment in water distribution networks

Postprint (published version

A fully data-driven approach for leak localization in water distribution networks

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper presents a data-driven technique for the localization of leaks in water distribution networks (WDN). The methodology requires hydraulic data, i.e., pressure measurements from a set of sensors installed throughout the network and topological information. Therefore, the hydraulic model of the WDN is not necessary for its operation. The hydraulic state of the complete set of nodes of the network is approximated by means of a graph-based interpolation technique. Then, a set of candidates where the leak can be located is achieved by comparing the computed states for both the leaky and nominal cases. The methodology is applied to a case study based on a real network, providing and discussing several graphical results and key performance indicators.The authors want to thank the RIS3CAT Utilities 4.0 SENIX project (COMRDI16-1-0055), as well as the Spanish national project DEOCS (DPI2016-76493-C3-3-R) and the Spanish State Research Agency through the María de Maeztu Seal of ExcelPeer ReviewedPostprint (author's final draft

Pumps condition assessment in water distribution networks

This paper presents a method for the detection of faults in electrical pumps. The method relies on the computation of two features, the pump efficiency and the hydraulic balance, that present reference values during healthy pump operation and change when the pump is affected by a fault. In this paper, the CUSUM Change Detection Test and the Mann-Whitney Change Point Method are proposed as change detection algorithms to process both features. The method has been applied to a real installation with several pumps and the results are reported in the paper.Peer ReviewedPostprint (published version

Optimizing operating rules of multiple source water supply systems in terms of system reliability and resulting operating costs

This Presentation is brought to you for free and open access by the City College of New York at CUNY Academic Works. It has been accepted forinclusion in International Conference on Hydroinformatics by an authorized administrator of CUNY Academic Works. For more information, pleasecontact [email protected] and operation of a multiple-objective multisource water supply system from the point of view of the conjunctive use of water sources is a very complex problem whose solution is not just obtained using analytical models but also through a negotiation process among stakeholders and in which Public Bodies have a main role. For these reasons, this problem has been addressed using conservative approaches based on simulation models or simulation–linear optimization models parameterized using few parameters which, in general, are already covered by existing generalized modelling tools using a longer or shorter trial and error process. However, these conservative approaches have drawbacks and constraints when dealing with certain complexities of water supply systems (i.e.: non-linearity, uncertainty or stochastic nature) that may prevent them of finding an optimal solution. This paper identifies and tests suitable simulation-optimization approaches found in existing generalized modeling tools for optimizing operating rules of multisource water supply systems in terms of system guarantee and resulting operating costs. The main purpose is to find out whether these approaches are already covering the decision support needs of managers, Public Bodies or other stakeholders involved in the operation of these systems, or ‘ad-hoc’ tools may be needed.Peer ReviewedPostprint (published version

Leakage detection and localization method based on a hybrid inverse/direct modelling approach suitable for handling multiple-leak scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. Nonetheless, the assumption of single-leak scenarios is usually considered and may not hold in real applications. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios in a large class of water distribution networks. This method can be seen as an upgrade of a direct-modeling approach in which a global search method based on Genetic Algorithms (GAs) has been integrated in order to estimate the water loss hotspots and their size. This is an inverse / direct modelling method which seeks to take benefit from both approaches: the exploration capability of GAs and the straightforwardness and reliability offered by the availability of an accurate hydraulic model. The application of the resulting method in a district metered area of the Barcelona water distribution network is provided and discussed.Peer ReviewedPostprint (author's final draft