Application of Artificial Intelligence for the Assessment of the Status of Power Transformers

The dissolved gas analysis (DGA) a non-destructive test procedure, has been in vogue for a long time now, for assessing the status of power and related transformers in service. An early indication of likely internal faults that may exist in Transformers has been seen to be revealed, to a reasonable degree of accuracy by the DGA. The data acquisition and subsequent analysis needs an expert in the concerned area to accurately assess the condition of the equipment. Since the presence of the expert is not always guaranteed, it is incumbent on the part of the power utilities to requisition a well planned and reliable artificial expert system to replace, at least in part, an expert. This paper presents the application of ordered ant miner (OAM) classifier for the prediction of involved fault. Secondly, the paper also attempts to estimate the remaining life of the power transformer as an extension to the elapsed life estimation method suggested in the literature.