Aiming at the imperfection and limitation of the conventional transformer fault diagnosis method in practical applications

the hybrid algorithm which combines the improved particle swarm optimizationalgorithm based on simulation annealing（SAPSO） thought with error back-propagation （BP） algorithm is used to train neural network. The hybrid algorithm can effectively avoid the defects of independently training neural network in conventional BP algorithm and PSO algorithm

and can be used to analyze dissolved gas in transformer for intelligent fault diagnosis. The experimental results show that SAPSO-BP hybrid algorithm has a faster convergence speed than BP and PSO-BP algorithms

and gains higher diagnosis accuracy.