Application of a wavelet neural network approach to detect stator winding short circuits in asynchronous machines

Introduction. Nowadays, fault diagnosis of induction machines plays an important role in industrial fields. In this paper, Artificial Neural Network (ANN) model has been proposed for automatic fault diagnosis of an induction machine. The aim of this research study is to design a neural network model that allows generating a large database. This database can cover maximum possible of the stator faults. The fault considered in this study take into account a short circuit with large variations in the machine load. Moreover, the objective is to automate the diagnosis algorithm by using ANN classifier. Method. The database used for the ANN is based on indicators which are obtained from wavelet analysis of the machine stator current of one phase. The developed neural model allows to taking in consideration imbalances which are generated by short circuits in the machine stator. The implemented mathematical model in the expert system is based on a three-phase model. The mathematical parameters considered in this model are calculated online. The characteristic vector of the ANN model is formed by decomposition of stator current signal using wavelet discrete technique. Obtained results show that this technique allows to ensure more detection with clear evaluation of turn number in short circuit. Also, the developed expert system for the taken configurations is characterized by high precision.Вступ. Нині діагностика несправностей асинхронних машин відіграє значну роль у промисловості. У цій статті запропоновано модель штучної нейронної мережі для автоматичної діагностики несправностей асинхронної машини. Метою цього дослідження є розробка моделі нейронної мережі, що дозволяє генерувати велику базу даних. Ця база може охоплювати максимально можливі несправності статора. Несправності, розглянуті у цьому дослідженні, враховують коротке замикання при великих коливаннях навантаження машини. Крім того, мета полягає в тому, щоб автоматизувати алгоритм діагностики за допомогою класифікатора штучної нейронної мережі. Метод. База даних, що використовується для штучної нейронної мережі, заснована на показниках, отриманих в результаті вейвлет-аналізу струму статора машини однієї фази. Розроблена нейронна модель дозволяє враховувати дисбаланси, що виникають при коротких замиканнях у статорі машини. Реалізована математична модель в експертній системі ґрунтується на трифазній моделі. Математичні параметри, що враховуються в цій моделі, розраховуються онлайн. Характеристичний вектор моделі штучної нейронної мережі формується шляхом розкладання сигналу струму статора з використанням вейвлет-дискретного методу. Отримані результати показують, що дана методика дозволяє забезпечити більше виявлення з чіткою оцінкою числа витків при короткому замиканні. Також розроблена експертна система для конфігурацій, що приймаються, відрізняється високою точністю

Aerodynamic analysis models for vertical-axis wind turbines

This work details the progress made in the development of aerodynamic models for studying Vertical-Axis Wind Turbines (VAWT’ s) with particular emphasis on the prediction of aerodynamic loads and rotor performance as well as dynamic stall simulations. The paper describes current effort and some important findings using streamtube models, 3-D viscous model, stochastic wind model and numerical simulation of the flow around the turbine blades. Comparison of the analytical results with available experimental data have shown good agreement

A Dialogue between the Hypoxia-Inducible Factor and the Tumor Microenvironment

The hypoxia-inducible factor is the key protein responsible for the cellular adaptation to low oxygen tension. This transcription factor becomes activated as a result of a drop in the partial pressure of oxygen, to hypoxic levels below 5% oxygen, and targets a panel of genes involved in maintenance of oxygen homeostasis. Hypoxia is a common characteristic of the microenvironment of solid tumors and, through activation of the hypoxia-inducible factor, is at the center of the growth dynamics of tumor cells. Not only does the microenvironment impact on the hypoxia-inducible factor but this factor impacts on microenvironmental features, such as pH, nutrient availability, metabolism and the extracellular matrix. In this review we discuss the influence the tumor environment has on the hypoxia-inducible factor and outline the role of this factor as a modulator of the microenvironment and as a powerful actor in tumor remodeling. From a fundamental research point of view the hypoxia-inducible factor is at the center of a signaling pathway that must be deciphered to fully understand the dynamics of the tumor microenvironment. From a translational and pharmacological research point of view the hypoxia-inducible factor and its induced downstream gene products may provide information on patient prognosis and offer promising targets that open perspectives for novel “anti-microenvironment” directed therapies

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Search for direct stau production in events with two hadronic tau-leptons in root s=13 TeV pp collisions with the ATLAS detector

A search for the direct production of the supersymmetric partners ofτ-leptons (staus) in final stateswith two hadronically decayingτ-leptons is presented. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of139fb−1, recorded with the ATLAS detector at the LargeHadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected StandardModel background is observed. Limits are derived in scenarios of direct production of stau pairs with eachstau decaying into the stable lightest neutralino and oneτ-lepton in simplified models where the two staumass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidencelevel for a massless lightest neutralino

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Oxygen Tension Regulates Pancreatic β-Cell Differentiation Through Hypoxia-Inducible Factor 1α

International audienceThese data demonstrate that beta-cell differentiation is controlled by pO2 through HIF1alpha. Modifying pO2 should now be tested in protocols aiming to differentiate beta-cells from embryonic stem cells