Transformers Health Index Assessment Based on Neural-Fuzzy Network

Emran Jawad Kadim, Norhafiz Azis, Jasronita Jasni, Siti Anom Ahmad and Mohd Aizam Talib
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Emran Jawad Kadim: Centre for Electromagnetic & Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Norhafiz Azis: Centre for Electromagnetic & Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Jasronita Jasni: Centre for Electromagnetic & Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Siti Anom Ahmad: Department of Electrical and Electronic Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Mohd Aizam Talib: TNB Research Sdn Bhd, Kajang 43000, Selangor, Malaysia

Energies, 2018, vol. 11, issue 4, 1-14

Abstract: In this paper, an assessment on the health index (HI) of transformers is carried out based on Neural-Fuzzy (NF) method. In-service condition assessment data, such as dissolved gases, furans, AC breakdown voltage (ACBDV), moisture, acidity, dissipation factor (DF), color, interfacial tension (IFT), and age were fed as input parameters to the NF network. The NF network were trained individually based on two sets of data, known as in-service condition assessment and Monte Carlo Simulation (MCS) data. HI was also obtained from the scoring method for comparison with the NF method. It is found that the HI of transformers that was obtained by NF trained by MCS method is closer to scoring method than NF trained by in-service condition assessment method. Based on the total of 15 testing transformers, NF trained by MCS data method gives 10 transformers with the same assessments as scoring method as compared to eight transformers given by NF trained by in-service condition data method. Analysis based on all 73 transformers reveals that 62% of transformers have the same assessments between NF trained by MCS data and scoring methods.

Keywords: health index (HI); Neural-Fuzzy (NF); condition assessment; transformers (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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