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

Djaidir, Benrabeh; Hafaifa, Ahmed; Guemana, Mouloud; Kouzou, Abdellah

doi:10.2478/ijame-2020-0048

Cited by 3 publications

(1 citation statement)

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“…Recent works have focused on diagnostic approaches for rotating machines, integrating vibration analysis based on input-output data. For example, the work of Benrabeh Djaidir et al [4] proposed an approach for detecting the vibration faults of a turbine through the behavior analysis of the input/output operating data of the rotating machine. This enables the improvement of vibration diagnosis strategy with better detection precision in real-time applications.…”

Section: Introductionmentioning

confidence: 99%

ARMAX-based identification and diagnosis of vibration behavior of gas turbine bearings

Mahroug,

Khaldi,

Guemana

et al. 2023

Diagnostyka

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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.

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Section: Introductionmentioning

confidence: 99%