Based on the data of dissolved gas analysis (DGA), fuzzy cluster analysis (FCA) technique is applied to identify the fault patterns of power transformers in this paper. FCA consists of some trial and instructive strategies absorbing usefulexperiences from the mid-results. Its clustering centers are dynamic, as a result, the approach can classify and recombine different samples successfully. Compared with the conventional methods, it reveals the practical advantages of unsupervised systems, including the ability to produce categories without supervision.
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