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Diagnostic maintenance of naval turbochargers
A method for the automatic condition monitoring of rotors with journal bearings is presented and applied to a specific naval turbocharger. Trying to combine only the advantages of some very popular computational tools - such as theoretical simulations, measurements and signal processing - together with the neural networks, the proposed method promises better physics-based and more detailed diagnosis in quantification of the faults. Several difficulties in setting up the neural networks and in the development of theoretical models have been encountered, due to complexity of the problem, but the results are very promising. However, it is essential that the full nonlinear hydrodynamic equations should be also included in order to obtain a more realistic model of the journal bearings' transient behaviour.
Diagnostic maintenance of naval turbochargers
A method for the automatic condition monitoring of rotors with journal bearings is presented and applied to a specific naval turbocharger. Trying to combine only the advantages of some very popular computational tools - such as theoretical simulations, measurements and signal processing - together with the neural networks, the proposed method promises better physics-based and more detailed diagnosis in quantification of the faults. Several difficulties in setting up the neural networks and in the development of theoretical models have been encountered, due to complexity of the problem, but the results are very promising. However, it is essential that the full nonlinear hydrodynamic equations should be also included in order to obtain a more realistic model of the journal bearings' transient behaviour.
Diagnostic maintenance of naval turbochargers
Pantelelis, N.G. (author) / Kanarachos, A.E. (author) / Gotzias, N. (author)
Measurement and Control ; 34 ; 101-102
2001
2 Seiten, 3 Quellen
Article (Journal)
English
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