<abstract xmlns="http://www.w3.org/1999/xhtml"><p>During the gas turbine exploitation the presence of small defects can cause very high vibration amplifications, localized on the components of this rotating machine. For this, a diagnostic process is necessary for decision-making during the monitoring of failures caused by vibration phenomena, which consists in observing the system by comparing its current data with the data coming from a normal operation. These indicators help engineer to determine the symptoms for the failing components of the system. This work deals with problems related to these vibrations, with the aim of developing a system of detection of failures using dynamic neural networks approach. The originality of this contribution is to calculate the various alarms based on this system which used the determined vibration models in order to ensure a reliable and safe operation of the gas compression installation using the examined gas turbine.</p></abstract>

During the gas turbine exploitation the presence of small defects can cause very high vibration amplifications, localized on the components of this rotating machine. For this, a diagnostic process is necessary for decision-making during the monitoring of failures caused by vibration phenomena, which consists in observing the system by comparing its current data with the data coming from a normal operation. These indicators help engineer to determine the symptoms for the failing components of the system. This work deals with problems related to these vibrations, with the aim of developing a system of detection of failures using dynamic neural networks approach. The originality of this contribution is to calculate the various alarms based on this system which used the determined vibration models in order to ensure a reliable and safe operation of the gas compression installation using the examined gas turbine.

Detection and Modeling Vibrational Behavior of a Gas Turbine Based on Dynamic Neural Networks Approach

Strojnícky časopis - Journal of Mechanical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

During the gas turbine exploitation the presence of small defects can cause very high vibration amplifications, localized on the components of this rotating...

Detection and Modeling Vibrational Behavior of a Gas Turbine Based on Dynamic Neural Networks Approach

Online veröffentlicht: 06. Dez. 2018

Seitenbereich: 143 - 166

DOI: https://doi.org/10.2478/scjme-2018-0032

Schlüsselwörter
Gas turbine, vibrations monitoring, model based faults detection, dynamic neural networks

© 2018 Mohamed Benrahmoune, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Detection and Modeling Vibrational Behavior of a Gas Turbine Based on Dynamic Neural Networks Approach

Online veröffentlicht: 06. Dez. 2018

Seitenbereich: 143 - 166

DOI: https://doi.org/10.2478/scjme-2018-0032

SchlüsselwörterGas turbine, vibrations monitoring, model based faults detection, dynamic neural networks

© 2018 Mohamed Benrahmoune, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Gas turbine, vibrations monitoring, model based faults detection, dynamic neural networks