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

Genetic identification, origin and sanitary status of grapevine cultivars (Vitis vinifera L.) grown in Babar, Algeria

This research focused on present grapevine biodiversity of neglected cultivars grown in 'Babar' region, Northeastern Algeria. The obtained results demonstrate the complex, rich, and even surprising inheritance of grapevine biodiversity in such a small region, with currently residual viticulture practiced only for direct consumption. Babar is one of the oldest inhabited areas in Algeria and part of the Atlas Mountains, considered very favorable for wild and cultivated vine growing since protohistoric times. Thirty-seven vines from the traditional growing area were analyzed using nuclear microsatellite (SSR) markers for cultivar identification and RT-qPCR analysis for virus detection and sanitary status evaluation. As a result, thirteen different genotypes were found, most of them showing a very good sanitary status, then constituting a valuable biological source for clonal selection. A close relatedness was evidenced with some Mediterranean varieties, resulting from previous exchanges of grapevine cultivars in the past. Furthermore, the present study highlighted the existence of three new genotypes, highly probably autochthonous of Babar region, with proposed names 'Babari', 'Babar-Algeria', and 'Amesski-Babar'. They could represent unique Algerian varieties, probably preserved over time. The conservation of these endangered genotypes is highly recommended

Analisis Data pada Jaringan Sensor Nirkabel Menggunakan Metode Support Vector Machine

The aims of this research are to implement Support Vector Machine for analyze abnormal data on sensor network and evaluate the implementation result. The data collection in the research were done through the searching of related libraries and software evaluate/testing. In this research, temperature, wind speed, and humidity tested using three kernels (linear, Gaussian, and polynomial). Evaluation result show that the implementation of Support Vector Machine can perform the best data validity analysis using Gaussian Kernel with the percentage of average accuracy, temperature 97.83%, humidity 94.5325%, and wind speed 96.93% for weather data 20-28 May and July 28-August 10, 2015. Meanwhile, for weather data June 5-6, 2017 obtained the percentage of average accuracy of temperature 92.855% and humidity 92.43%

Frequency- and time-domain investigation of the dynamic properties of interlayer-exchange-coupled Ni81Fe19/Ru/Ni81Fe19 thin films

Pulsed inductive microwave magnetometer (PIMM), conventional ferromagnetic resonance (FMR), and vector network analyzer FMR (VNA-FMR) have been used for complementary studies of the various excited modes in exchange-coupled NiFe(30 nm)/Ru(d(Ru))/NiFe(30 nm) films with variable Ru thicknesses d(Ru). For antiferromagnetically coupled layers, two modes, which vary in their relative intensity as a function of the bias field, are detected. These two modes, which are observable simultaneously over a limited range of the bias field with PIMM, are identified as optic and acoustic modes. The mode frequencies and the interlayer exchange coupling are found to oscillate as a function of the Ru layer thickness with a period of 8.5 A. The frequency oscillations of the optic mode are coupling dependent, while those of the acoustic mode are indirectly related to coupling via the canting angle of the layer magnetizations below the saturation. Comparison between PIMM and VNA-FMR in terms of frequency of modes shows good agreement, but the optic mode is observed over a wider field range with VNA-FMR. Furthermore, we clearly observed different behaviors of the FMR linewidths as a function of the spacer thickness for the optic and acoustic modes. In addition, perpendicular standing spin waves have been studied as a function of coupling. The FMR linewidth of the different modes increases with the microwave frequency and typical damping constants of alpha=0.0073 have been measured. The effect of the pulse field amplitudes on the properties of the various excited modes has been simulated and studied experimentally

Ferromagnetic resonance in evaporated Co∕Si(100) and Co∕glass thin films

International audienc

Virtual load machine as test environment for industrial storage applications

The market share of renewable energy is rising all over the world and leads to a more and more volatile energy supply. The challenge of keeping supply and demand constantly balanced is getting more complex and dynamic. Large scale energy consumers like industrial facilities need to take on an active role in the energy system and adapt their energy consumption to the energy availability. Denoted as energy flexibility this approach controls the energy consumption by changing e.g. the production plan. Storage technologies decouple offer and demand of energy, that end-users are enabled to adapt their energy consumption. Testing new applications for storages can be technologically demanding and is associated with high costs. This paper proposes a hardware in the loop test environment, with which hardware integrations and control strategies of electric storage systems can be tested on a small scale