Mathematical model for evaluating the natural vibration frequency of gas-turbine engine disks with small change of web thickness

Luk'yanov, V. S.; Khodakov, G. A.

doi:10.1007/bf01524148

Cited by 1 publication

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“…Indeed, in several industrial applications there are methods which have already been developed previously for improving the gas turbine monitoring systems to give the status and operating information of a gas turbine from these signals vibrations [1][2][3][4][5]. Nonetheless, these methods have several disadvantages in their starting to integrate the source of vibration into these monitoring systems.…”

Section: Introductionmentioning

confidence: 99%

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

Benrahmoune

Hafaifa

Guemana

et al. 2018

Strojnícky Časopis - Journal of Mechanical Engineering

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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.

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