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Automated Prediction of Critical States of Turbogenerators During Thermal Expansion of a Rotor and a Stator Based on a Recurrent Neural Network
2018
International Journal of Engineering & Technology
The present article is devoted to the development of a method and its software implementation for forecasting the critical states of a turbogenerator and its design elements that arise during starting-up & adjustment works and stopping a turbine. The method is based on a short-term prediction of the image of the spectrogram of vibrations during thermal expansion of the rotor and stator. The dependence of the increase in the vibration level in the spectrum with the failure of the turbogenerator
doi:10.14419/ijet.v7i4.38.24316
fatcat:4m7ibhw5j5eu5bx4iztgut6wy4