Recognition of PD faults using chaos mathematics

Knowledge of Partial Discharges (PD) is important to diagnose and predict the health of insulation. The PD phenomenon is highly complex and seems to be random in its occurrence. It has been indicated by A.A. Paithankar and A.D.Mokashi (1997) using the model proposed by Lutz Niemeyer (1995), that the apparently random behavior of PD is actually due to the chaotic dynamics of the PD process. This paper indicates the possible use of chaos mathematics for the recognition and distinction between the PD faults. Chaos refers to a state where the predictive abilities of a systems future are lost and the system is rendered aperiodic. The analysis of PD using deterministic chaos comprises of the study of the basic system dynamics of the PD phenomenon. This involves the construction of the PD attractor in state space and quantify it by means of dynamic qualifiers using chaos algorithms. The evolution of the PD system is studied using time series as well as state space graphs and chaotic attractors have been determined for ellipsoidal voids in epoxy and corona discharge occurring in overhead cables. A dynamic qualifier called Lyapunov exponent which describes dynamic behavior of the attractor qualitatively as well as quantitatively has been evaluated for the above two cases. It has been shown that the numerical value of the Lyapunov exponent in both tie cases differs. Capacity dimension and Information dimension are also evaluated. Discrimination of PD faults on the basis of Lyapunov Exponent and such other qualifiers is possible. To the knowledge of the authors this is the first attempt to show chaos mathematics as a promising way to analyze PD and recognize PD faults