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In this study we investigate the possibility of rotor broken bar fault detection in squirrel cage induction generator of a wind turbine using spectral analysis of the stator currents. The numerical method, presented in this work, based on the Hilbert Huang transform shows the possibility of improving the detection of faults in electrical machines. Using the Hilbert Huang transform analyses the stator...
Vibration analysis is a highly responsive tool in the rotating machine industry, making it possible to highlight the symptoms of anomalies affecting this type of machine. This work proposes the use of these tools to develop a strategy for monitoring a gas turbine used in a natural gas transportation in Algeria, based on vibrations analysis and detection of an examined gas turbine, the proposed approach...
In this paper we have introduced a new parametric output feedback control design algorithm based on the Block similarity transformations. It is needed that complete Block controllability and Block observability be a necessary and sufficient conditions for the proposed method in order to assign whole set of poles via the output feedback for linear multivariable system. The parameterization of the output...
In this work the approach of active fault tolerant control system applied to a turbocharger is proposed. Where the main aim is the development of synthesis of this control in the fault diagnosis. The control approach developed in this work is based on a fuzzy approach for the detection and the isolation of faults affecting the studied turbocharger. Whereas, the linear sliding mode control theory is...
This paper presents an approach of rotating machinery fault diagnosis based on Nonlinear Autoregressive with External (Exogenous) Input NARX neural networks. This tool is trained on the real data obtained from the sensors at bearing and it is used to ensure the faults diagnosis of the most damages that can appear in the system of gas turbine. Indeed the artificial neural networks provide an effective...
This paper presents some experimental results obtained for the diagnosis of the rotor broken bars in three identical squirrel cage induction generators by the analysis of stator current signatures MCSA using Periodogram, Covariance, and MUSIC techniques respectively. These signatures are detected from DSP of the test bench implemented at the laboratory.
Rotating machines are widely used in the industry; all these machines in operation produce vibrations phenomena caused by dynamic forces generated in moving parts of these equipments. This work propose the development of fault diagnosis system for the vibration detection and isolation based on artificial intelligence using artificial neural networks, applied to a gas turbine system, in order to secure...
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