Wound-Rotor Induction Generator Inter-Turn Short-Circuits Diagnosis Using a New Digital Neural Network

Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art

“…In recent works, artificial neural networks (ANN) are applied to the FD of inter-turn short-circuits in induction machines in different applications. In [37], an ANN approach is applied to a wound-rotor induction generator. The authors apply a classical ANN with back-propagation, but it is trained directly by digital signals coming from sensors, leading to a diagnostic system with a simplified architecture that could be set up using low-cost hardware, such as field-programmable gate arrays (FPGAs).…”

Big Data Decision Making Based on Predictive Data Analysis Using DEVS Simulations

“…From a M&S perspectives the following tasks have been performed: (i) Development of a DEVSimPy Neural Network (NN) components library for manipulating neural nets by extending the work already presented in [6] in order to deal with the problematics raised by the Good Barber application; (ii) Development of a set of DEVSimPy plug-in allowing to facilitate the design of NN configuration, training and validation when dealing with the Big Data.…”

Diagnosis of Rotor and Stator Asymmetries in Wound-Rotor Induction Machines Under Nonstationary Operation Through the Instantaneous Frequency

“…Recently, this task has been addressed by several researchers; some works aim to adapt MCSA methods for diagnosing wind generators, assuming steady state or limited and slow variations of the working load conditions as in [11], [12]. Nevertheless, these approaches cannot be considered as a general method of diagnostic, because they are subjected to a conceptual drawback: they apply a steady state based methodology to machines which usually undergo continuously variable working conditions.…”