ARMAX-based identification and diagnosis of vibration behavior of gas turbine bearings
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Laboratory of Mechanics, Physics and Mathematical Modelling, University of Medea, 26000, Medea, Algeria
Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Djelfa, Algeria
Department of Electrical and Electronics Engineering, Nisantasi University, 34398 Sarıyer, İstanbul, Turkey
Faculty of Science and Technology, University of Bordj Bou Arreridj, 34030 DZ, Algeria
Submission date: 2023-03-06
Final revision date: 2023-07-18
Acceptance date: 2023-08-16
Online publication date: 2023-09-08
Corresponding author
Mouloud Guemana   

Laboratory of Mechanics, Physics and Mathematical Modelling, University of Medea, 26000, Medea, Algeria
Diagnostyka 2023;24(3):2023310
Parametric identification approaches play a crucial role in the control and monitoring of industrial systems. They facilitate the identification of system variables and enable the prediction of their evolution based on the input-output relationship. In this study, we employ the ARMAX approach to accurately predict the dynamic vibratory behavior of MS5002B gas turbine bearings. By utilizing real input-output data obtained from their operation, this approach effectively captures the vibration characteristics of the bearings. Additionally, the ARMAX technique serves as a valuable diagnostic tool for the bearings, enhancing the quality of identification of turbine variables. This enables continuous monitoring of the bearings and real-time prediction of their behavior. Furthermore, the ARMAX approach facilitates the detection of all potential vibration patterns that may occur in the bearings, with monitoring thresholds established by the methodology. Consequently, this enhances the availability of the bearings and reduces turbine downtime. The efficacy of the proposed ARMAX approach is demonstrated through comprehensive results obtained in this study. Robustness tests are conducted, comparing the real behavior observed through various probes with the reference model, thereby validating the approach.
This research, focused on the identification of MS5002B gas turbine variables for the diagnosis of their bearings using the ARMAX approach, was conducted at the Hassi R'Mel Gas Center by the Joint Gas Turbine Research Team in collaboration with the Applied Automation and Industrial Diagnostics Laboratory at the University of Djelfa, Algeria. The authors of this paper extend their heartfelt gratitude to all those who contributed to the successful completion of this work, particularly the staff of the Hassi R'Mel Gas Center in Algeria.
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