Decision making framework for power transformer Dissolved Gas Analysis on the basis of Dempster-Shafer theoretic approach

Abstract

Dissolved Gas Analysis (DGA) is usually performed for power transformer condition based maintenance (CBM) activities. In reality, the interpretation of DGA data is complex and done through several knowledge sources. Lack of information within these knowledge sources necessitates an information fusion methodology. Constructed upon DempsterShafer (DS) theoretic approach, this paper proposes a novel interpretation rule and algorithm. Weibull functions were utilized to quantify the degree of belief in major fault according to respective DGA parameters. Threshold belief mass (THB) that distinguishes incipient fault from major fault, which is located within the interval of degree of belief in major fault were observed. In this paper, based on minimum threshold values, a novel rule termed as Threshold Belief Mass (THB) interpretation rule is proposed and compared with Dempster's and Yager's combination rule. Furthermore, from the result of THB interpretation rule and belief or plausibility function, different level of transformer's condition is suggested. Several operational and maintenance decision-making proposal are introduced for a system operator with respect to the belief and plausibility function. In summary, the new method enables a system operator to interpret DGA data more systematically.

Review of Artificial Intelligence Techniques Application to Dissolved Gas Analysis on Power Transformer

“…In this approach, based on minimum threshold values, a novel rule termed as Threshold Belief Mass (THB) interpretation rule is proposed and compared with Dempster's and Yager's combination rule. In fact, this new approach enables a system operator to interpret DGA data more systematically [45].…”

“…In this approach, based on minimum threshold values, a novel rule termed as Threshold Belief Mass (THB) interpretation rule is proposed and compared with Dempster's and Yager's combination rule. In fact, this new approach enables a system operator to interpret DGA data more systematically [45].New Quantum Neural Network (QNN) was applied to diagnosis the transformer fault by employing the DGA data. The advantage of the QNN model based on quantum phase in dealing with uncertain, ambiguous and cross fault data are verified by the practical engineering application [46].…”

Power transformer diagnosis decision-making based on unified combination rule and maximax-maximin criterion

“…Yager proposed a combination rule that is free from the disadvantages of Demspter's combination rule, but it may not explicitly tell the decision maker the most probable hypothesis of power transformer's condition when the residual ignorance is large [1]. On the other hand, Inagaki [5] has shown that various combination rule which ranges from Yager's combination rule to extrapolation combination rule exist, termed as the unified combination rules.…”

“…[1] discusses the interpretation of DGA based on threshold belief mass interpretation rule and compare them with Dempster and Yager combination rule.…”

“…To deal with this uncertainty, Dempster-Shafer (DS) Theory is often utilized for the fusion of evidence obtained from various DGA diagnosis [1,2]. In the Dempster-Shafer theoretic approach, several rules for combining the evidence were proposed [3,4,5], amongst them is unified combination rule by Inagaki [5].…”