An Associative Binary Particle Swarm Optimization for the Diagnosis of Transformer Failure
Anurag Tamrakar1, V. B. Reddy2
1Anurag Tamrakar, Research Scholar, Department of Electrical and Electronics, Swami Vivekanand University, Sagar (Madhya Pradesh), India.
2V.B. Reddy, Associate Professor, Department of Electrical and Electronics, Swami Vivekanand University, Sagar (Madhya Pradesh), India.
Manuscript received on 18 December 2018 | Revised Manuscript received on 27 December 2018 | Manuscript published on 30 December 2018 | PP: 67-71 | Volume-8 Issue-2, December 2018 | Retrieval Number: B5554128218/18©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper an associative binary particle swarms optimization (BPSO) for the diagnosis of transformer failure. In this approach transformer oil gas have been considered for the fault diagnosis so that proper functionality of transformer can be enhanced and the efficiency of transformer can be improved. For this dissolve gas analysis (DGA) and IEC standards have been used for weight assignment of different gas ratios. Rule mining have been applied where these standards fails in the weight assignments. Finally based on the rules associates with different gas ratios have been analyzed separately for each clusters. Finally based on BPSO faults have been diagnosed in several iterations. The results clearly indicate that our approach has better fault diagnosis and individual gas associations.
Keywords: BPSO, Associations Rules, DGA and IEC Standards.
Scope of the Article: Discrete Optimization