Ardyono Priyadi, Margo Pujiantara, Mauridhi Hery Purnomo : Transformer monitoring using harmonic current based on wavelet transformation and probabilistic neural network (PNN)

Ardyono Priyadi ST, M.Eng
Ir. Margo Pujiantara MT
Prof.Dr.Ir. Mauridhi Hery Purnomo M.Eng.



Published in

The 1st International Conference on Information Technology, Computer, and Electrical Engineering

External link



Seminar Internasional


Monitoring Current Harmonic wavelet PNN


Today, Transformer monitoring is urgently needed. This come from the reality that Indonesian Electrical Company could not know the condition of the transformer which was installed. The transformer is known damaged after something happen with the transformer. The Indonesian electrical company does some maintenance for the transformer, but this maintenance is only for checking the transformer is working well or not. The Indonesian electrical company could not check how long the transformer will be working well, how old the transformer and how is the condition of the transformer oil. Monitoring without directly touching the transformer is a new method. This method also can be applied simply by Indonesian electrical company. To monitor a transformer without touching directly required a long and continuously research. Age classification based on harmonic current transformer is one way to monitor the transformer without touching it. Harmonic currents filtered using wavelet transform and the results will be classified using PNN.