A Markovian jump system approach for the estimation and adaptive diagnosis of decreased power generation in wind farms

In this study, a Markovian jump model of the power generation system of a wind turbine is proposed and the authors present a closed-loop model-based observer to estimate the faults related to energy losses. The observer is designed through an H∞-based optimisation problem that optimally fixes the trade-off between the observer fault sensitivity and robustness. The fault estimates are then used in data-based decision mechanisms for achieving fault detection and isolation. The performance of the strategy is then ameliorated in a wind farm (WF) level scheme that uses a bank of the aforementioned observers and decision mechanisms. Finally, the proposed approach is tested using a well-known benchmark in the context of WF fault diagnosis

Robust estimation and diagnosis of wind turbine pitch misalignments at a wind farm level

Wind turbine pitch misalignments provoke aerodynamic asymmetries which cause severe damage to the turbine. Hence, it is of interest to develop fault tolerant strategies to cope with pitch misalignments. Fault tolerant strategies require the information regarding the diagnosis and the estimation of the faults. However, most existing works focus only on open-loop misalignment diagnosis and do not provide robust fault estimates. In this work, we present a novel strategy to both estimate and diagnose pitch misalignments. The proposed strategy is developed at a wind farm level and it exploits altogether the information provided by the temporal and spatial relations of the turbines in the farm. Fault estimation is first addressed with a closed-loop switched observer. This observer is robust against disturbances and it adapts to the varying conditions along the wind turbine operation range. Fault diagnosis is then achieved via statistical-based decision mechanisms with adaptive thresholds. Both the observer and the decision mechanisms are designed to guarantee the desired performance. Introducing some restrictions over the number of simultaneous faulty turbines in the farm, the proposed approach is ameliorated via a bank of the aforementioned observers and decision mechanisms. Finally, the strategies are tested using a well-known wind farm benchmark

Trade-offs on fault estimation via proportional multiple-integral and multiple-resonant observers for discrete-time systems

The authors develop a fault estimation strategy which is based on a novel proportional multiple-integral (PMI) and multiple-resonant observer. This observer is an extension of the well-known PMI observer and it is able to estimate from low to high-frequency fault signals. The proposed estimation strategy is applied to discrete-time systems which are affected by faults and stochastic noises. We present a multi-objective design strategy of the observer that fixes the trade-offs between practical engineering parameters regarding the noise attenuation and the ability to track each kind of fault dynamics considered by the augmented observer. They study the influence of the order of the observer on the steady-state and transient performance of the estimation of different types of faults. Finally, a numerical example is given to illustrate the effectiveness of the proposed observer, design and characterisation

Banks of estimators and decision mechanisms for pitch actuator and sensor FE in wind turbines

Comunicació presentada a SAFEPROCESS 2018. 10th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (Warsaw, Poland, 29–31 August 2018)Wind turbines are prone to multiple different faults and input observability conditions are not always guaranteed for these faults. In such cases, it is not possible to build estimators which provide appropriate fault estimates for its further use in active FTC schemes such as fault tolerant MPC. Provided that these faults are generally non-simultaneous, we make use of this property for building banks of model-based estimators and statistical-based decision mechanisms that provide appropriate fault estimates for enhancing active FTC capabilities. We apply these strategies to a well-known wind turbine FDI and FTC benchmark and we show the effectiveness of the bank of estimators and decision mechanisms for estimating the faults occurring in the pitch system of a wind turbine

Multiobjective performance-based designs in fault estimation and isolation for discrete-time systems and its application to wind turbines

In this work, we develop a performance-based design of model-based observes and statistical-based decision mechanisms for achieving fault estimation and fault isolation in systems affected by unknown inputs and stochastic noises. First, through semidefinite programming, we design the observers considering different estimation performance indices as the covariance of the estimation errors, the fault tracking delays and the degree of decoupling from unknown inputs and from faults in other channels. Second, we perform a co-design of the observers and decision mechanisms for satisfying certain trade-off between different isolation performance indices: the false isolation rates, the isolation times and the minimum size of the isolable faults. Finally, we extend these results to a scheme based on a bank of observers for the case where multiple faults affect the system and isolability conditions are not verified. To show the effectiveness of the results, we apply these design strategies to a well-known benchmark of wind turbines which considers multiple faults and has explicit requirements over isolation times and false isolation rates

Actuator Fault Tolerant Control Proposal for PI Controlled SISO Systems

Comunicació presentada a SAFEPROCESS 2018. 10th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (Warsaw, Poland, 29–31 August 2018)In this work, we develop a control structure which can be added to an existing closed loop in order to mitigate the effect of actuator faults. We analyze the initial performance of the closed loop in terms of robustness and time response under references, faults and measurement noises. In the design of the proposed active fault tolerant control structure, we keep the initial robustness and time response to references. At the same time, we try to improve some performance indices under faults at the cost of a higher control action activity caused by the measurement noises that affect the system. The design of the controller depends on a unique parameter so it can be easily understood. We show that although the response under step faults becomes oscillatory, the active fault tolerant structure reduces the integral of the absolute value of the tracking error under step faults and it attenuates the effect of ramp faults in steady state. Several examples show the goodness and drawbacks of the approach and show some aspects to be considered in the design

Estimation of Nonstationary Process Variance in Multistage Manufacturing Processes Using a Model-Based Observer

In this paper, we propose a recursive algorithm to estimate the process variance in multistage manufacturing or assembly processes. We use a replicated model that includes the process variance to be estimated as a time-varying state that changes slowly. For this model, we develop an estimation strategy including tuning parameters that play a direct role in the tradeoff between the estimation accuracy and the adaptation to changes. We also develop a statistical confidence interval for the estimations which enhances the decision of whether the process variances have changed. Unlike other batch methods in the literature, our proposal is computed recursively, and it allows us to tune the tradeoff between the convergence speed and the accuracy without modifying the sample size, which only contains the data of the last manufactured piece

Optimal fault estimation and diagnosis strategies: bridging the gap between theory and practice

This thesis addresses some issues arisen from the application of estimation-based fault diagnosis strategies to different practical systems such as industrial pipe networks, multistage manufacturing processes, wind turbines and wind farms. With this aim, the thesis presents different fault estimators relying on model-based augmented observers and, also, various fault evaluators that process the fault estimates provided by the observers in threshold-based decision mechanisms. The thesis devotes an important effort to the design of these estimation-based FD strategies. The thesis presents the design of fault estimators and evaluators which allow specifying requirements over fault diagnosis performance parameters. The thesis also presents an enhanced form of augmented observers: proportional multiple-integral and multiple-resonant. Also, the thesis presents a probabilistic design approach that optimally deals with the trade-offs arisen from the structural complexity of augmented observers.Esta tesis aborda algunos de los problemas derivados de la aplicación de estrategias de estimación de fallos a diferentes sistemas prácticos como redes de tuberías industriales, procesos de fabricación multietapa, aerogeneradores y parques eólicos. Con este objetivo, la tesis presenta diferentes estimadores de fallo basados en observadores aumentados y, también, varios evaluadores de fallo que procesan las estimaciones proporcionadas por los observadores en mecanismos de decisión con umbrales. La tesis se centra en el diseño de estas estrategias de diagnóstico de fallos basadas en estimación. Se presentan diferentes diseños de estimadores y evaluadores que permiten especificar requisitos sobre parámetros que describen el desempeño de la estrategia en el diagnóstico de fallos. La tesis también presenta una forma mejorada de observadores aumentados: observadores proporcionales múltiple-integrales y múltiple-resonantes. Asimismo, se presenta un enfoque de diseño probabilístico que aborda los compromisos derivados de la complejidad estructural de los observadores aumentados.Programa de Doctorat en Tecnologies Industrials i Material

Enhancement of wind projects viability by optimal strategies of wind turbines predictive maintenance

Treball final de Màster Universitari en Eficiència Energètica i Sostenibilitat. Codi: SIV034. Curs acadèmic 2014-2015Today, wind energy contributes to world’s power production in a big percentage. Simultaneously, the size of standard wind turbines increases periodically. Due to their high prices, the reliability of big turbines should be high in order to ensure maximal energetic production by guaranteed short downtimes. A way to achieve this requirement consists in introducing advanced predictive maintenance systems based on fault detection, isolation, and recovery strategies into the turbines. The state-of-the-art of actual wind turbines reveals the use of fault detection strategies which are simple and often conservative, and so is the fault compensation system. In order to improve the on-time of the turbine, the need of advanced fault detection, isolation, and accommodation schemes arises. The main objective of this work is to provide an optimal fault diagnosis strategy that ensures an appropriate behaviour of wind turbines with reference to faults. This design will be tested on an international wind turbines fault diagnosis benchmark.En la actualidad, los aerogeneradores contribuyen a la producci´on energ´etica mundial en un porcentaje elevado. Al mismo tiempo, el tama˜no de una turbina e´olica standard tiende a aumentar. Los generadores e´olicos de gran tama˜no son caros y, por tanto, se espera que su fiabiliad sea elevada para que produzcan la m´axima energ´ıa posible; as´ı, ´estos deben tener tiempos de parada cortos. Una manera de asgurar este objetivo consiste en introducir avanzados sistemas de mantenimineto predictivo basados en la detecci´on, aislamiento y acomodamiento de fallos en los aerogeneradores. En la mayor parte de los aerogeneradores industriales los esquemas de detecci´on y acomodamiento son simples y, muchas veces, conservativos. En consecuencia, existe la necesidad de introducir esquemas m´as avanzados para aumentar la productividad de estas turbinas. El objetivo principal de este trabajo es propocionar una estartegia ´optima de diagn´ostico de fallos que asegura un correcto funcionamiento de la turbian en relaci´on a los fallos. Este dise˜no se comprobar´a en un modelo de referencia internacional para el diagn´ostico de fallos en aerogneradores

Moodle questionnaires as a self-assessment tool for meeting the challenges of diversity in students' background knowledge

Comunicació presentada al ICERI 2018 11th annual International Conference of Education, Research and Innovation (Seville, Spain. 12-14 November, 2018)Process Automation and Advanced Control is a subject of the master’s degree in Industrial Engineering from the Universitat Jaume I de Castelló that seeks to develop the students’ ability to design automated production systems and advanced process controllers. In order to properly acquire the specific competences of this master’s degree subject, the students should master some basic concepts of control systems that are generally acquired at a bachelor’s degree level. The teachers of the subject find that the background knowledge of the master students is diverse because the students have studied different bachelor’s degrees at different European universities. The content of the subject being dense, the lecturers have little room for manoeuvre in order to review and reinforce this necessary prior knowledge during the lessons. In this work, we present a tool that allows the students to self-assess their prior knowledge. The tool has been implemented in Moodle and it consists of a variety of questionnaires with instantaneous feedback that guides each student on the learning materials that he should review in order to fill his gaps in background knowledge