PSNet
Neural Networks to Analyze Surface Tracking on Solid Insulators, by
Agur, Aukland,Varlow and Emin, Univ of Manchester, UK.
Abstract:
Surface tracking on solid insulators is one of the most severe
breakdown mechanisms associated with polymeric materials under long term
service conditions. A wide range of relays can detect failure in a
transmission line and prevent a total breakdown in the systems, but die to
the non-healing characteristics of solid insulations, in most cases it
might be too late to save the insulator after tracking initiation and
growth. The method described here is employed mainly in detecting several
conditions, such as discharges, leakage current,dry conditions, severe
damage and tracking initiation. Initially a BPN (back propagation network)
type NN (neural network) is trained with different signal types. Due to
the nature of NN, which always require similar values of input nodes, the
system uses FFT (fast Fourier transform) of the input signal, which might
have high amplitude frequency components other that th fundamental
frequency depending on the condition of the surface. The system works on a
real time basis and warns the user with the first indication of sever
damage on the surface and can protect the insulator from excessive damage.
IEEE Transactions on Dielectrics and Electrical Insulation, Vol 4,
No 6, Dec 1997 p 763
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