Search results for "Power engineering"
showing 6 items of 126 documents
Quantitative Rotor Broken Bar Evaluation in Double Squirrel Cage Induction Machines under Dynamic Operating Conditions
2013
Advanced monitoring techniques leading to fault diagnosis and prediction of induction machine faults, operating under non-stationary conditions have gained strength because of its considerable influence on the operational continuation of many industrial processes. In case of rotor broken bars, fault detection based on sideband components issued from currents, flux, instantaneous control or power signals under different load conditions, may fail due to the presence of inter-bar currents that reduce the degree of rotor asymmetry, especially for double squirrel cage induction motors. But the produced core vibrations in the axial direction, can be investigated to overcome the limitation of the …
Transient stability simulation of a fixed speed wind turbine by Matlab/Simulink
2007
This paper describes the dynamic behavior of a typical fixed speed wind turbine connected to the grid; the model is developed in the simulation tool Matlab/Simulink and created as a modular structure. The pitch control system is used for stabilization of the wind turbine at grid faults. In this way, voltage stability of the system with grid-connected wind turbines can be improved by using blade-angle control for a temporary reduction of the wind turbine power during a short-circuit fault in the grid. This paper shows a new variable control for maintaining of voltage stability, when a three-phase fault is applied close to the wind turbine and cleared by disconnecting the affected line. In th…
Emulating the Effects of Radiation-Induced Soft-Errors for the Reliability Assessment of Neural Networks
2021
International audience; Convolutional Neural Networks (CNNs) are currently one of the most widely used predictive models in machine learning. Recent studies have demonstrated that hardware faults induced by radiation fields, including cosmic rays, may significantly impact the CNN inference leading to wrong predictions. Therefore, ensuring the reliability of CNNs is crucial, especially for safety-critical systems. In the literature, several works propose reliability assessments of CNNs mainly based on statistically injected faults. This work presents a software emulator capable of injecting real faults retrieved from radiation tests. Specifically, from the device characterisation of a DRAM m…
Bearing fault detection based on time-frequency representations of vibration signals
2015
To prevent failures of a rolling bearing in the gearbox drive system, acceleration sensors are used to detect fault-related signals of the bearing. It is a big challenge to observe and identify signals caused by bearing defects in the time domain or the frequency spectrum by a conventional Fourier analysis. The time-frequency representation of the fault-related signals implemented by the windowed Fourier transform is studied in this work. It is shown that the fault characteristic frequencies can be clearly identified in the time-frequency spectrum if a fault occurs in the bearing of the gearbox at different speeds. Otherwise, the shaft frequency and its multiples are the main harmonics in t…
On the distribution of lightning current among interconnected grounding systems in medium voltage grids
2018
This paper presents the results of a first investigation on the effects of lightning stroke on medium voltage installations' grounding systems, interconnected with the metal shields of the Medium Voltage (MV) distribution grid cables or with bare buried copper ropes. The study enables us to evaluate the distribution of the lightning current among interconnected ground electrodes in order to estimate if the interconnection, usually created to reduce ground potential rise during a single-line-to-ground fault, can give place to dangerous situations far from the installation hit by the lightning stroke. Four different case studies of direct lightning stroke are presented and discussed: (1) two …
Fault diagnosis of induction motors broken rotor bars by pattern recognition based on noise cancelation
2014
Current signal monitoring (CSM) can be used as an effective tool for diagnosing broken rotor bars fault in induction motors. In this paper, fault diagnosis and classification based on artificial neural networks (ANNs) is done in two stages. In the first stage, a filter is designed to remove irrelevant fault components (such as noise) of current signals. The coefficients of the filter are obtained by least square (LS) algorithm. Then by extracting suitable time domain features from filter's output, a neural network is trained for fault classification. The output vector of this network is represented in one of four categories that includes healthy mode, a 5 mm crack on a bar, one broken bar, …