Vibration Analysis in Turbomachines Using Machine Learning Techniques

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  •   Allan Alves Pinheiro

  •   Iago Modesto Brandao

  •   Cesar Da Costa

Abstract

This study proposes a method for diagnosing faults in turbomachines using machine learning techniques. In this study, a support vector machine-SVM algorithm is proposed for fault diagnosis of rotor rotation imbalance. Recently, support vector machines (SVMs) have become one of the most popular classification methods in vibration analysis technology. Axis unbalance defect is classified using support vector machines. The experimental data is derived from the turbomachine model of the rigid-shaft rotor and the flexible bearings, and the experimental setup for vibration analysis. Several situations of unbalance defects have been successfully detected.


Keywords: Machine Learning;, Fault Diagnosis, Vibration Analysis, Fault Classification

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How to Cite
[1]
Pinheiro, A., Brandao, I. and Da Costa, C. 2019. Vibration Analysis in Turbomachines Using Machine Learning Techniques. European Journal of Engineering Research and Science. 4, 2 (Feb. 2019), 12-16. DOI:https://doi.org/10.24018/ejers.2019.4.2.1128.