Detection of Vibrations Defects in Gas Transportation Plant Based on Input / Output Data Analysis: Gas Turbine Investigations-Reference-Cited by-同舟云学术

Detection of Vibrations Defects in Gas Transportation Plant Based on Input / Output Data Analysis: Gas Turbine Investigations

Published:2020-11-26 Issue:4 Volume:25 Page:42-58
ISSN:2353-9003
Container-title:International Journal of Applied Mechanics and Engineering
language:en
Short-container-title:

Author:

Djaidir B.¹,Hafaifa A.¹,Guemana M.²,Kouzou A³

Affiliation:

1. Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology , University of Djelfa , 17000 DZ , Algeria , Gas Turbine Joint Research Team , University of Djelfa , 17000 DZ , Algeria

2. Gas Turbine Joint Research Team , University of Djelfa , , Algeria

3. Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology , University of Djelfa , 17000 DZ , Algeria

Abstract

Abstract In oil and gas industrial production and transportation plants, gas turbines are considered to be the major pieces of equipment exposed to several unstable phenomena presenting a serious danger to their proper operation and to their exploitation. The main objective of this work is to improve the competitiveness performance of this type of equipment by analyses and control of the dynamic behaviors and to develop a fault monitoring system for the equipment exposed and subject to certain eventual anomalies related to the main components, namely the shaft and the rotors. This study will allow the detection and localization of vibration phenomena in the studied gas turbine based on the input / output data.

Publisher

Walter de Gruyter GmbH

Subject

Fluid Flow and Transfer Processes,Transportation,Civil and Structural Engineering

Link

https://www.sciendo.com/pdf/10.2478/ijame-2020-0048

Reference24 articles.

1. [1] Bendjama H., Boucherit M.S., Bouhouche S. and Mansour M. (2010): Vibration signal analysis using wavelet transform –PCA-NN technique for fault diagnosis in rotating machinery. – The Mediterranean Journal of Measurment and Control, vol.6, No.4, pp.145-154.

2. [2] Khadersab A. and Shivakumar S. (2010): Vibration analysis techniques for rotating machinery and its effect on bearing faults. – Procedia Manufacturing, vol.20, pp.247-252.

3. [3] Madhavan S., Rajeev Jain, Sujatha C. and Sekhar A.S. (2014): Vibration based damage detection of rotor blades in a gas turbine engine. – Engineering Failure Analysis, vol.46, pp.26-39.10.1016/j.engfailanal.2014.07.021

4. [4] Paolo Pennacchi and Andrea Vania (2008): Diagnostics of a crack in a load coupling of a gas turbine using the machine model and the analysis of the shaft vibrations. – Mechanical Systems and Signal Processing, vol.22, No.5, pp.1157-1178.10.1016/j.ymssp.2007.10.005

5. [5] Sandeep Kumar, Niranjan Roy and Ranjan Ganguli (2007): Monitoring low cycle fatigue damage in turbine blade using vibration characteristics. – Mechanical Systems and Signal Processing, vol.21, No.1, pp.480-501.10.1016/j.ymssp.2005.02.011

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