320 research outputs found

    Aspects of structural health and condition monitoring of offshore wind turbines

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    Wind power has expanded significantly over the past years, although reliability of wind turbine systems, especially of offshore wind turbines, has been many times unsatisfactory in the past. Wind turbine failures are equivalent to crucial financial losses. Therefore, creating and applying strategies that improve the reliability of their components is important for a successful implementation of such systems. Structural health monitoring (SHM) addresses these problems through the monitoring of parameters indicative of the state of the structure examined. Condition monitoring (CM), on the other hand, can be seen as a specialized area of the SHM community that aims at damage detection of, particularly, rotating machinery. The paper is divided into two parts: in the first part, advanced signal processing and machine learning methods are discussed for SHM and CM on wind turbine gearbox and blade damage detection examples. In the second part, an initial exploration of supervisor control and data acquisition systems data of an offshore wind farm is presented, and data-driven approaches are proposed for detecting abnormal behaviour of wind turbines. It is shown that the advanced signal processing methods discussed are effective and that it is important to adopt these SHM strategies in the wind energy sector

    Setting priorities in health care organizations: criteria, processes, and parameters of success

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    BACKGROUND: Hospitals and regional health authorities must set priorities in the face of resource constraints. Decision-makers seek practical ways to set priorities fairly in strategic planning, but find limited guidance from the literature. Very little has been reported from the perspective of Board members and senior managers about what criteria, processes and parameters of success they would use to set priorities fairly. DISCUSSION: We facilitated workshops for board members and senior leadership at three health care organizations to assist them in developing a strategy for fair priority setting. Workshop participants identified 8 priority setting criteria, 10 key priority setting process elements, and 6 parameters of success that they would use to set priorities in their organizations. Decision-makers in other organizations can draw lessons from these findings to enhance the fairness of their priority setting decision-making. SUMMARY: Lessons learned in three workshops fill an important gap in the literature about what criteria, processes, and parameters of success Board members and senior managers would use to set priorities fairly

    Towards population-based structural health monitoring, part IV : heterogeneous populations, transfer and mapping

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    Population-based structural health monitoring (PBSHM) involves utilising knowledge from one set of structures in a population and applying it to a different set, such that predictions about the health states of each member in the population can be performed and improved. Central ideas behind PBSHM are those of knowledge transfer and mapping. In the context of PBSHM, knowledge transfer involves using information from a structure, defined as a source domain, where labels are known for a given feature, and mapping these onto the unlabelled feature space of a different, target domain structure. If the mapping is successful, a machine learning classifier trained on the transformed source domain data will generalise to the unlabelled target domain data; i.e. a classifier built on one structure will generalise to another, making Structural Heath Monitoring (SHM) cost-effective and applicable to a wide range of challenging industrial scenarios. This process of mapping features and labels across source and target domains is defined as domain adaptation, a subcategory of transfer learning. However, a key assumption in conventional domain adaptation methods is that there is consistency between the feature and label spaces. This means that the features measured from one structure must be the same dimension as the other (i.e. the same number of spectral lines of a transmissibility), and that labels associated with damage locations, classification and assessment, exist on both structures. These consistency constraints can be restrictive, limiting to which types of population domain adaptation can be applied. This paper, therefore, provides a mathematical underpinning for when domain adaptation is possible in a structural dynamics context, with reference to topology of a graphical representation of structures. By defining when conventional domain adaptation is applicable in a structural dynamics setting, approaches are discussed that could overcome these consistency restrictions. This approach provides a general means for performing transfer learning within a PBSHM context for structural dynamics-based features

    Three novel and the common Arg677Ter RP1 protein truncating mutations causing autosomal dominant retinitis pigmentosa in a Spanish population

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    BACKGROUND: Retinitis pigmentosa (RP), a clinically and genetically heterogeneous group of retinal degeneration disorders affecting the photoreceptor cells, is one of the leading causes of genetic blindness. Mutations in the photoreceptor-specific gene RP1 account for 3–10% of cases of autosomal dominant RP (adRP). Most of these mutations are clustered in a 500 bp region of exon 4 of RP1. METHODS: Denaturing gradient gel electrophoresis (DGGE) analysis and direct genomic sequencing were used to evaluate the 5' coding region of exon 4 of the RP1 gene for mutations in 150 unrelated index adRP patients. Ophthalmic and electrophysiological examination of RP patients and relatives according to pre-existing protocols were carried out. RESULTS: Three novel disease-causing mutations in RP1 were detected: Q686X, K705fsX712 and K722fsX737, predicting truncated proteins. One novel missense mutation, Thr752Met, was detected in one family but the mutation does not co-segregate in the family, thereby excluding this amino acid variation in the protein as a cause of the disease. We found the Arg677Ter mutation, previously reported in other populations, in two independent families, confirming that this mutation is also present in a Spanish population. CONCLUSION: Most of the mutations reported in the RP1 gene associated with adRP are expected to encode mutant truncated proteins that are approximately one third or half of the size of wild type protein. Patients with mutations in RP1 showed mild RP with variability in phenotype severity. We also observed several cases of non-penetrant mutations

    The development of endomycorrhizal root systems VIII. Effects of soil phosphorus and fungal colonization on the concentration of soluble carbohydrates in roots

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    Concentrations of phosphorus in shoot and soluble carbohydrates (fructose, glucose, sucrose and fructans) in root were measured in non-mycorrhizal and vesicular-arbuscular (VA) mycorrhizal (Glomus mosseae) leek plants (Allium porrum) raised at six concentrations of soil phosphate. In conditions when an increased concentration of soil phosphate reduced VA mycorrhizal infection, the concentrations of soluble carbohydrates in the root were at a maximum. Therefore the hypothesis that greater concentrations of soluble carbohydrates in roots favour VA mycorrhizal infection is discounted. There was a specific effect of VA mycorrhizas, in that infected roots contained a larger concentration of sucrose than did uninfected roots, in plants with similar phosphorus concentrations in dry matter of shoots. We conclude, first, that increased phosphorus supply from either phosphate addition to soil or VA mycorrhizal infection increases concentration of soluble carbohydrates in leek roots and, secondly, that the VA mycorrhizal root behaves as a particularly strong physiological sink when there is an excess concentration of sucrose in the host

    Modeling Transmission Dynamics and Control of Vector-Borne Neglected Tropical Diseases

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    Neglected tropical diseases affect more than one billion people worldwide. The populations most impacted by such diseases are typically the most resource-limited. Mathematical modeling of disease transmission and cost-effectiveness analyses can play a central role in maximizing the utility of limited resources for neglected tropical diseases. We review the contributions that mathematical modeling has made to optimizing intervention strategies of vector-borne neglected diseases. We propose directions forward in the modeling of these diseases, including integrating new knowledge of vector and pathogen ecology, incorporating evolutionary responses to interventions, and expanding the scope of sensitivity analysis in order to achieve robust results

    A Critical Review on the Structural Health Monitoring Methods of the Composite Wind Turbine Blades

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    With increasing turbine size, monitoring of blades becomes increasingly im-portant, in order to prevent catastrophic damages and unnecessary mainte-nance, minimize the downtime and labor cost and improving the safety is-sues and reliability. The present work provides a review and classification of various structural health monitoring (SHM) methods as strain measurement utilizing optical fiber sensors and Fiber Bragg Gratings (FBG’s), active/ pas-sive acoustic emission method, vibration‒based method, thermal imaging method and ultrasonic methods, based on the recent investigations and prom-ising novel techniques. Since accuracy, comprehensiveness and cost-effectiveness are the fundamental parameters in selecting the SHM method, a systematically summarized investigation encompassing methods capabilities/ limitations and sensors types, is needed. Furthermore, the damages which are included in the present work are fiber breakage, matrix cracking, delamina-tion, fiber debonding, crack opening at leading/ trailing edge and ice accre-tion. Taking into account the types of the sensors relevant to different SHM methods, the advantages/ capabilities and disadvantages/ limitations of repre-sented methods are nominated and analyzed
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