Fault Diagnosis of Transformer Based on Chaotic Bats Algorithm Optimizing Fuzzy Petri Net

A267 at the problem of low accuracy and long training time in the traditional intelligent algorithm of tr ansformer fault diagnosis, a fault diagnosis method based on chaotic bats algorithm optimization fuzzy Petri net (CBA-FPN) is proposed. DGA was considered as feature input, the parameters of FPN were coded into bats, and then the optimal parameters of FPN were founded by chaotic bat optimization algorithm. The fuzzy Petri net model was used to diagnose the transformer according to the optimal parameters. The simulation results show that the proposed algorithm has faster convergence speed and the higher correctness than the method of BP Optimized FPN (BP-FPN) and BA Optimized FPN network(BA-FPN), and has certain application valu e in the transformer fault diagnosis.