Monitoring of high-speed shaft of gas turbine using artificial neural networks: predictive model application

• Autorzy: Rahmoune M. B. , Hafaifa A. , Abdellah K. , Chen X. Q.
• Języki publikacji: EN

Abstrakty

EN

The automatic engineering known a very rapid progress with the consequent development of numerical methods and computer systems, by the growth of computational capacity. In this context, this work proposes a strategy of predictive control of the high-pressure shaft speed of a gas turbine using artificial neural networks in order to monitor the vibratory behavior of this rotating machine. This approach makes it possible to ensure the stability of this turbine under real conditions and to detect any deviation of their dynamic behavior from the margin of safety. This approach makes it possible to include the control limitations on the turbine variables in the modeling step of the high-speed shaft speed controller.

Słowa kluczowe

EN

monitoring; gas turbine; vibrations; artificial neural networks; predictive model

PL

turbina gazowa; monitoring; drgania; sztuczna sieć neuronowa; model predykcyjny

• Wydawca: Polskie Towarzystwo Diagnostyki Technicznej
• Czasopismo: Diagnostyka
• Rocznik: 2017
• Tom: Vol. 18, No. 4
• Strony: 3--10
• Opis fizyczny: Bibliogr. 21 poz., rys., wykr.

Twórcy

autor

Rahmoune M. B.

• Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria

autor

Hafaifa A.

• Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria

autor

Abdellah K.

• Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria

autor

Chen X. Q.

• Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand

Bibliografia

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