The health index scheme can be the most fundamental tool that unifies all transformer condition status information into a singular\noutcome, thereby enhancing the power transformer asset management and life longevity strategies. This study aims at establishing\na multiple parameter-dependent transformer health index estimation model cascaded with a fuzzy logic inference system. This\nstrategy is centered on the effect of dynamic loading regime, varying hotspot temperatures and multiple attesting results of the\ninsulation system. Furthermore, a nonintrusive degree of polymerization (DP) model based on furans and carbon oxide ratios as\nDP pointers is also factored in developing the health index model. The general outcome of the health index depends on entirely\nconsidered elements, but not on any isolated attribute. Data obtained from in-service transformers were used to validate the\nproposed model. The outcome of the model mirrors the practical condition of the evaluated transformers. Therefore, the proposed\nhealth index model can be a vital tool to asset managers and power utilities.
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