Fault Diagnosis of a Wind Turbine Simulated Model via Neural Networks

The fault diagnosis of wind turbine systems has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of wind turbines, and it proposes viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves a data-driven approach, as it represents an effective tool for coping with a poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the data-driven proposed solution relies on neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen network architecture belongs to the nonlinear autoregressive with exogenous input topology, as it can represent a dynamic evolution of the system along time. The developed fault diagnosis scheme is tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are compared with those of other control strategies, coming from the related literature. Moreover, a Monte Carlo analysis validates the robustness of the proposed solutions against the typical parameter uncertainties and disturbances

Fault Diagnosis of a Wind Turbine Simulated Model via Neural Networks

The fault diagnosis of wind turbine systems has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of wind turbines, and it proposes viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves a data-driven approach, as it represents an effective tool for coping with a poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the data-driven proposed solution relies on neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen network architecture belongs to the nonlinear autoregressive with exogenous input topology, as it can represent a dynamic evolution of the system along time. The developed fault diagnosis scheme is tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are compared with those of other control strategies, coming from the related literature. Moreover, a Monte Carlo analysis validates the robustness of the proposed solutions against the typical parameter uncertainties and disturbances

Active Fault Tolerant Control of a Wind Farm System

In order to enhance the 'sustainability’ of offshore wind farms, thus skipping unplanned maintenance operations and costs, that can be important for offshore systems, the earlier management of faults represents the key point. Therefore, this work studies the development of an adaptive sustainable control scheme with application to a wind farm benchmark consisting of nine wind turbine systems. They are described via their nonlinear models, as well as the wind and wake effects among the wind turbines of the wind park. The fault tolerant control strategy uses the recursive estimation of the faults provided by nonlinear estimators designed via a nonlinear differential algebraic tool. This aspect of the study, together with the more straightforward solution based on a data-driven scheme, is the key issue when on-line applications are proposed for a viable implementation of the proposed solutions

Frequency-tunable metamaterials using broadside-coupled split ring resonators

We present frequency tunable metamaterial designs at terahertz (THz) frequencies using broadside-coupled split ring resonator (BC-SRR) arrays. Frequency tuning, arising from changes in near field coupling, is obtained by in-plane horizontal or vertical displacements of the two SRR layers. For electrical excitation, the resonance frequency continuously redshifts as a function of displacement. The maximum frequency shift occurs for displacement of half a unit cell, with vertical displacement resulting in a shift of 663 GHz (51% of f0) and horizontal displacement yielding a shift of 270 GHz (20% of f0). We also discuss the significant differences in tuning that arise for electrical excitation in comparison to magnetic excitation of BC-SRRs

Optically thin composite resonant absorber at the near-infrared band: a polarization independent and spectrally broadband configuration

Cataloged from PDF version of article.We designed, fabricated, and experimentally characterized thin absorbers utilizing both electrical and magnetic impedance matching at the near-infrared regime. The absorbers consist of four main layers: a metal back plate, dielectric spacer, and two artificial layers. One of the artificial layers provides electrical resonance and the other one provides magnetic resonance yielding a polarization independent broadband perfect absorption. The structure response remains similar for the wide angle of incidence due to the sub-wavelength unit cell size of the constituting artificial layers. The design is useful for applications such as thermal photovoltaics, sensors, and camouflage. (C)2011 Optical Society of Americ

Software defect prediction: do different classifiers find the same defects?

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.During the last 10 years, hundreds of different defect prediction models have been published. The performance of the classifiers used in these models is reported to be similar with models rarely performing above the predictive performance ceiling of about 80% recall. We investigate the individual defects that four classifiers predict and analyse the level of prediction uncertainty produced by these classifiers. We perform a sensitivity analysis to compare the performance of Random Forest, Naïve Bayes, RPart and SVM classifiers when predicting defects in NASA, open source and commercial datasets. The defect predictions that each classifier makes is captured in a confusion matrix and the prediction uncertainty of each classifier is compared. Despite similar predictive performance values for these four classifiers, each detects different sets of defects. Some classifiers are more consistent in predicting defects than others. Our results confirm that a unique subset of defects can be detected by specific classifiers. However, while some classifiers are consistent in the predictions they make, other classifiers vary in their predictions. Given our results, we conclude that classifier ensembles with decision-making strategies not based on majority voting are likely to perform best in defect prediction.Peer reviewedFinal Published versio

Hardware-In-The-Loop Assessment of a Fault Tolerant Fuzzy Control Scheme for an Offshore Wind Farm Simulator

To enhance both the safety and the efficiency of offshore wind park systems, faults must be accommodated in their earlier occurrence, in order to avoid costly unplanned maintenance. Therefore, this paper aims at implementing a fault tolerant control strategy by means of a data-driven approach relying on fuzzy logic. In particular, fuzzy modelling is considered here as it enables to approximate unknown nonlinear relations, while managing uncertain measurements and disturbance. On the other hand, the model of the fuzzy controller is directly estimated from the input-output signals acquired from the wind farm system, with fault tolerant capabilities. In general, the use of purely nonlinear relations and analytic methods would require more complex design tools. The design is therefore enhanced by the use of fuzzy model prototypes obtained via a data-driven approach, thus representing the key point if real- time solutions have to implement the proposed fault tolerant control strategy. Finally, a high- fidelity simulator relying on a hardware-in-the-loop tool is exploited to verify and validate the reliability and robustness characteristics of the developed methodology also for on-line and more realistic implementations

Bacterial cellulose-lactoferrin as an antimicrobial edible packaging

Bacterial cellulose (BC) films from two distinct sources (obtained by static culture with Gluconacetobacter xylinus ATCC 53582 (BC1) and from a commercial source (BC2)) were modified by bovine lactoferrin (bLF) adsorption. The functionalized films (BC+bLF) were assessed as edible antimicrobial packaging, for use in direct contact with highly perishable foods, specifically fresh sausage as a model of meat products. BC+bLF films and sausage casings were characterized regarding their water vapour permeability (WVP), mechanical properties, and bactericidal efficiency against two food pathogens, Escherichia coli and Staphylococcus aureus. Considering their edibility, an in vitro gastrointestinal tract model was used to study the changes occurring in the BC films during passage through the gastrointestinal tract. Moreover, the cytotoxicity of the BC films against 3T3 mouse embryo fibroblasts was evaluated. BC1 and BC2 showed equivalent density, WVP and maximum tensile strength. The percentage of bactericidal efficiency of BC1 and BC2 with adsorbed bLF (BC1+bLF and BC2+bLF, respectively) in the standalone films and in inoculated fresh sausages, was similar against E. coli (mean reduction 69 % in the films per se versus 94 % in the sausages) and S. aureus (mean reduction 97 % in the films per se versus 36 % in the case sausages). Moreover, the BC1+bLF and BC2+bLF films significantly hindered the specific growth rate of both bacteria. Finally, no relevant cytotoxicity against 3T3 fibroblasts was found for the films before and after the simulated digestion. BC films with adsorbed bLF may constitute an approach in the development of bio-based edible antimicrobial packaging systems.The authors would like to acknowledge Portuguese Foundation for Science and Technology (Fundação para a Ciência e Tecnologia) for the research grants: Jorge Padrão SFRH/BD/64901/2009, Sara Gonçalves SFRH/BD/63578/2009, João Pedro Silva SFRH/BPD/ 64958/2009, Ana Cristina Pinheiro SFRH/BPD/101181/2014. V. Sencadas thanks support from the COST Action MP1206: “Electrospun nano-fibres for bio inspired composite materials and innovative industrial applications” and MP1301: “New Generation Biomimetic and Customized Implants for Bone Engineering”. The authors would also like to thank the co-funded by the Programa Operacional Regional do Norte (ON.2 e O Novo Norte), QREN, FEDER Projects “BioHealth e Biotechnology and Bioengineering approaches to improve health quality”, Ref. NORTE-07-0124- FEDER-000027; “BioInd e Biotechnology and Bioengineering for improved Industrial and Agro-Food processes”, REF. NORTE-07- 0124-FEDER-000028; Strategic Project PEST-C/FIS/UI607/2014; Matepro eOptimizing Materials and Processes”, ref. NORTE-07- 0124-FEDER-000037; Strategic Project PEst-OE/EQB/LA0023/2013 and project ref. RECI/BBB-EBI/0179/2012 (project number FCOMP- 01-0124-FEDER-027462). Finally, the authors thank the Fundação para a Ciência e Tecnologia for the strategic funding from the UID/ BIO/04469/2013 unit

A perspective on radical transformations to sustainability: resistances, movements and alternatives

A transformation to sustainability calls for radical and systemic societal shifts. Yet what this entails in practice and who the agents of this radical transformation are require further elaboration. This article recenters the role of environmental justice movements in transformations, arguing that the systemic, multi-dimensional and intersectional approach inherent in EJ activism is uniquely placed to contribute to the realization of equitable sustainable futures. Based on a perspective of conflict as productive, and a “conflict transformation” approach that can address the root issues of ecological conflicts and promote the emergence of alternatives, we lay out a conceptual framework for understanding transformations through a power analysis that aims to confront and subvert hegemonic power relations; that is, multi-dimensional and intersectional; balancing ecological concerns with social, economic, cultural and democratic spheres; and is multi-scalar, and mindful of impacts across place and space. Such a framework can help analyze and recognize the contribution of grassroots EJ movements to societal transformations to sustainability and support and aid radical transformation processes. While transitions literature tends to focus on artifacts and technologies, we suggest that a resistance-centred perspective focuses on the creation of new subjectivities, power relations, values and institutions. This recenters the agency of those who are engaged in the creation and recuperation of ecological and new ways of being in the world in the needed transformation

Degradation aspects of water formation and transport in Proton Exchange Membrane Fuel Cell: A review

This review paper summarises the key aspects of Proton Exchange Membrane Fuel Cell (PEMFC) degradation that are associated with water formation, retention, accumulation, and transport mechanisms within the cell. Issues related to loss of active surface area of the catalyst, ionomer dissolution, membrane swelling, ice formation, corrosion, and contamination are also addressed and discussed. The impact of each of these water mechanisms on cell performance and durability was found to be different and to vary according to the design of the cell and its operating conditions. For example, the presence of liquid water within Membrane Electrode Assembly (MEA), as a result of water accumulation, can be detrimental if the operating temperature of the cell drops to sub-freezing. The volume expansion of liquid water due to ice formation can damage the morphology of different parts of the cell and may shorten its life-time. This can be more serious, for example, during the water transport mechanism where migration of Pt particles from the catalyst may take place after detachment from the carbon support. Furthermore, the effect of transport mechanism could be augmented if humid reactant gases containing impurities poison the membrane, leading to the same outcome as water retention or accumulation. Overall, the impact of water mechanisms can be classified as aging or catastrophic. Aging has a long-term impact over the duration of the PEMFC life-time whereas in the catastrophic mechanism the impact is immediate. The conversion of cell residual water into ice at sub-freezing temperatures by the water retention/ accumulation mechanism and the access of poisoning contaminants through the water transport mechanism are considered to fall into the catastrophic category. The effect of water mechanisms on PEMFC degradation can be reduced or even eliminated by (a) using advanced materials for improving the electrical, chemical and mechanical stability of the cell components against deterioration, and (b) implementing effective strategies for water management in the cell