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DETERMINISTIC APPROACH AND NEURAL NETWORK APPROACH FOR STATOR SHORT CIRCUITS DIAGNOSIS IN INDUCTION MACHINES
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| Author(s) |
F. Filippetti; G. Franceschini; C. Tassoni; G. Gentile; S.Meo; A. Ometto; N. Rotondale |
| Abstract |
In this paper short circuits in stator windings of induction machines are considered. Two diagnostic approaches
are analysed. They are respectively based on different deterministic models of the faulted machine and on neural network techniques to represent the system behaviour. The deterministic faulted models have an increasing simplification level and consequently a decreasing effectiveness. About the neural network approach the crucial points are the input/output retrieving, the choice of input and output variables and the learning phase. The relevant performances obtained by means of
the two approaches are compared and discussed. |
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| Filename: | Unnamed file |
| Filesize: | 512.8 KB |
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| Type |
Members Only |
| Date |
Last modified 2015-12-14 by System |
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