Study on Power Transformer Faults Based on Neural Network Combined Plant Growth Simulation Algorithm

• DOI: 10.2174/2213275910666170502150006
• Publication Date: 2017-05-09T08:37:35Z
• Authors: Ying Xia; Bo Zhou; Mengxiong Lu; Chuanqing Sun
• Keywords: Power transmission; Power network

Background: In the modern age when electric power is one of major energies, electrical equipment and transformer are indispensable. Power an important transmission transformation in system. The failure may induce long-term supply interruption large economic loss. Therefore, diagnosis repair broken-down great urgency. This study developed a patent which could improve fault applicability reduce faults using plant growth simulation algorithm (PSGA) combination with neural network method. Methods: First all, improved PSGA model was established according to characteristics defects PSGA. Secondly, combined for analysis faults; back-propagation (BP) then as well given experiment. Results: Simulation results showed that such method accurately diagnose faults. Finally, internal transformers, recognition mathematical winding experimental simulation. indicated enough satisfy synthetic transformers. Conclusion: conclusion, provides effective theoretical basis fixing Keywords: Plant algorithm, network, transformer, study, transmission.