Combined Duval Pentagons: A Simplified Approach

Abstract

The paper describes a newly proposed combination of the two existing Duval Pentagons method utilized for the identification of mineral oil-insulated transformers. The aim of the combination is to facilitate automatic fault identification through computer programs, and at the same time, apply the full capability of both original Pentagons, now reduced to a single geometry. The thorough classification of a given fault (say, of the electrical or thermal kind), employing individual Pentagons 1 and 2, as originally defined, involves a complex geometrical problem that requires the build-up of a convoluted geometry (a regular Pentagon whose axes represent each of five possible combustible gases) to be constructed using computer language code and programming, followed by the logical localization of the geometrical centroid of an irregular pentagon, formed by the partial contribution of individual combustibles, inside two similar structures (Pentagons 1 and 2) that, nonetheless, have different classification zones and boundaries, as more thoroughly explained and exemplified in the main body of this article. The proposed combined approach results in a lower number of total fault zones (10 in the combined Pentagons against 14 when considering Pentagons 1 and 2 separately, although zones PD, S, D1 and D2 are common to both Pentagons 1 and 2), and therefore eliminates the need to solve for two separate Pentagons.

Application of Dissolved Gas Analysis in Assessing Degree of Healthiness or Faultiness with Fault Identification in Oil-Immersed Equipment

“…The last ratio R 4 when violated and used gives the DOF as expressed by Equation (12). A faulty apparatus with R 4 = 21 will have a DOF evaluated on this ratio as 1.1, meaning this equipment has suffered a Faulty (F) fault, whereas another piece of equipment with R 4 = 0.36 will have a DOF of 7.333, which is a More Faulty (MF) level of faulting.…”

“…Lastly, an extremely faulty fault plan requires an immediate shutdown to avoid catastrophic imminent failure such as an explosion. The results of 138 fault cases documented in references [3,12,25] were used to elaborate the applicability of this ideological concept. Other concepts used by researchers to estimate the degree of fault severity includes that given in [22,23], which estimates the faulty severity based on the energy of fault formation and that given by Prasojo et al in [24], which uses the gas level, gas rate, and fault type based on the Duval pentagon technique interpretation.…”

“…The fault identification was carried out using the numerical IEC three-gas ratio and two artificial intelligence techniques: fuzzy logic and fuzzy evidential reasoning. One hundred and thirty-eight fault cases of visually inspected and verified equipment found in references [3,12,25,36] were used for verification and comparison among these applied techniques. The outcome is as shown in Tables 7-10.…”

“…These are either conventional or unconventional tools. The most standardized conventional ones are the IEEE C75.104 method based on the major gases generated as given in reference [6], the three IEC gas ratios documented in [7], the Doernenburg and the Rogers gas ratios documented in [10], the CIGRE TF 15.01.01 ratios and concentrations thresholds in [11], and visual methods such as the popular Duval triangles 1-7, pentagons 1 and 2 [4,5], the recent combined pentagon in [12] and Diaa-Eldin pentagon proposed in 2015 [13]. None of the above conventional methods has yielded perfect results in fault analysis, prompting researchers to turn to unconventional techniques otherwise known as artificial intelligence (AI).…”

Fluid Degradation Measurement Based on a Dual Coil Frequency Response Analysis

“…Most of them are based on ratios of different compound concentrations, such as the Doernenberg or the Rogers' method. The Duval's triangle and pentagons combine several ratios to achieve a diagnostic about transformer oil degradation [17,18]. Another technique used to evaluate fluid degradation is ultraviolet spectrophotometry [19].…”