Assessment of utility of the corona audible signal in the diagnostic process of the technical condition of UHV transmission lines

The paper deals with application of neural network
techniques to recognition of typical damages of the transmission circuit
elements in UHV power lines. The damage indicator is the acoustic signal
generated by the corona effect, the intensity of which increases as a result of
damage or contamination of the conductor surface. The primary difficulty in the
diagnostic process is the necessity to distinguish between the signals generated
by the surface damages and contaminations. The problem can not be solved neither
by the analysis of RF interference signal nor by the classical methods of the
acoustic signal analysis. Particular attention has been focused on the
parametrization of the acoustic signal of corona effect and selection of
distinctive features, which could be useful in distinguishment of the origins of
the increased corona effect in dry conductor surface conditions. For that task
the aggregation analysis has been applied, in particular the possibilities
offered by "Statistica"[ampersand]reg; software package. The data used in the analysis has
been obtained from laboratory studies in Institute of Power Engineering in
Warsaw, where typical surface damages and contaminations of the transmission
line elements have been simulated. Keywords: corona noise, diagnosis, acoustics,
cluster analysis, neural network.