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Advanced analysis of the motor starting currents enables very reliable diagnostics of the rotor condition, providing immunity against the eventual false alarms obtained with the conventional MCSA. However, the application of this methodology has been mainly restricted to the case of line-started machines. Its extension to the cases of soft-started or inverted-fed motors has been barely investigated,...
This article presents a modified control strategy for a large input voltage range in an active-clamp soft switching converter. This control strategy is based on frequency modulation and allows a soft switching of all semiconductor devices on a large input voltage range. This frequency modulation also minimizes transformer loss without losing soft switching both on primary and secondary side of the...
Monitoring electrical motors in critical or sensitive environments is one of the major challenges of our era. This can be applied both in electric vehicles, hybrid and avionics. Therefore the development of tools, which are able to ensure continuity of service by identifying and predicting faults, is crucial to provide a reliable monitoring. This paper presents two methods based on Hidden Markov Models...
Advanced analysis of motor currents during transient operation has proven to be a valuable source of information to reach a reliable assessment of the rotor condition. This novel approach may help to overcome some of the drawbacks of the classical Motor Current Signature Analysis (MCSA). One of the advantages of the approach is the robustness obtained due to its twofold perspective: 1) Qualitative...
This paper deals with a photovoltaic system based on a Z-source DC-DC converter. This type of structure differs from a classical converter by the presence of a shoot-through duty cycle in comparison with the standard duty cycle. This recent topology, involving an X-shape LC impedance network, is attractive. So, in this application, the photovoltaic energy is stored in lead acid batteries thanks to...
Rolling element bearings are devices used in almost every electrical machine. Therefore, it is important to monitor and track the degradation of bearings. This paper presents a new approach to predict the degradation of bearings by a time series forecasting model called the neo-fuzzy neuron. The proposed approach uses the root mean square extracted from vibration signals as a health indicator. The...
In the last decade, the field of diagnosis has attracted the attention of many researchers, especially for the detection of faults in induction motors. The condition monitoring of induction motors is generally based on the analysis of signals coming from one or several sensors. This analysis is performed by the motor current signature analysis (MCSA) which is considered as the most popular fault detection...
Even if the asynchronous machine is widely used in industrial process under speed variable, we have to monitor the process which is composed of an inverter and a motor in an enclosed space. Thus, the stator current is not accessible and the AC supply line current is only available to monitor the system in comparison to a motor connected directly to the power supply. In this paper, we focus our attention...
As the induction motor takes a large place in industrial process, more than ever it is necessary to monitor the process. This motor can be connected to the lines or supplied by a voltage inverter converter. Whatever rugged the induction motor is several stresses could affect its live span. So it has to monitor in order to prevent the operator from the dangerousness. Many technics appeared based on...
This paper deals with a novel rotor-flux Kalman observer of a Dual Three-Phase Induction Machine. It will be shown analytically how this observer is built. This rotor-flux estimator can be used for the Direct Rotor Field-Oriented Control. A closed-loop control of this flux is therefore added. Simulation results shows the efficiency of this Kalman filter.
Accurate fault detection and diagnosis in complex systems is necessary for economic and security reasons. In this paper, we present a novel approach for fault detection and diagnosis based on Hidden Markov Models. This approach uses pattern recognition combining motor current signature analysis and multiple features extracted from transformations made on current and voltage signals in order to build...
In the last decade, the field of diagnosis has attracted the attention of many researchers, especially for the diagnosis of induction motors. This type of machine is widely used in industry because of its robustness and its specific power. Therefore, the monitoring and diagnosis of these motors become very important. This paper deals with the diagnosis of induction motor faults. The method is based...
The present paper focuses by means of an experimental study, on the effect of a bearing fault on the stator current signatures in induction motors. The variation in the amplitude of the characteristic components is not so significant. For that and in order to depict the presence of the fault harmonic signatures, the authors used the phase analysis of Hilbert transform applied on the spectrum modulus...
Most of rotor related faults in three-phase induction motors are due to broken rotor bars and end-ring defects. Nowadays Inductions motors are more frequently used with inverters which make the diagnosis process more complicated. Furthermore, some manufacturers of induction machines mount converters (i.e. rectifier and inverter) directly onto the machine, which makes the stator current unattainable...
In this paper, a new approach is applied to solve classification problems for the diagnosis of faults in induction motors. This new method finds its origins in works on the unsupervised classification algorithms based on ant clustering and the heuristic principles of the K-means algorithm and the principal components analysis (PCA). The main advantage is that requires no information about the system...
The present paper describes an analytical model of a squirrel cage induction machine based on the presentation of different machine inductances as Fourier series without any kind of reference frame transformation. By taking into account axial non uniformity due to slot skewing or asymmetrical static eccentricity, the proposed approach shows that this model is able to give important features on the...
This paper describes experimental results aiming at analyzing lithiumion batteries performances with aging, for different state of charge and temperatures. The results are provided from electrochemical impedance spectroscopy (EIS) measurements on new and aged cells. A climatic test chamber is used during experiments to simulate the conditions of the temperature. Experimental data are plotted over...
This paper proposes a new method for inductance calculation of induction motors (IM) based on the convolution theorem. The integral form leading to the inductance expressions is derived from the 2D modified winding function approach (2D-MWFA). As first application, a model allowing teeth saturation to be taken into account by the corresponding air-gap permeance variation is proposed. The work points...
This paper describes experimental results aiming at analyzing lithium-ion batteries performances with aging, for different state of charge and temperatures. The results are provided from electrochemical impedance spectroscopy (EIS) measurements on new and aged cells. A climatic test chamber is used during experiments to simulate the conditions of the temperature. Experimental data are plotted over...
This paper focuses on the tracking of faulty lines of induction motors operating under fault. The approach suggested in this paper deals with the particle swarm optimization to explore the search space which incorporates chaos. This one should be an opportunity to extract the principal faulty lines, in a current spectrum, dealing with a rotor broken bar whatever the motor operates at variable frequency...
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