Method for predicting concentration of dissolved gas in transformer oil based on PSO-LSTM

The invention discloses a method for predicting the concentration of dissolved gas in transformer oil based on PSO-LSTM. The method achieves the effective evaluation of the operation state of a transformer through the accurate prediction of the concentration of the dissolved gas in the transformer oil. The method comprises the steps of firstly, collecting online oil chromatography sample data of atransformer, determining state characteristic parameters of the data, performing normalization processing, and dividing a training set and a test set; secondly, constructing a long-term and short-term memory network prediction model, optimizing the long-term and short-term memory network prediction model through a particle swarm algorithm to obtain two optimal prediction model parameters, and reestablishing a long-term and short-term memory network model according to the obtained optimal prediction model parameters; and finally, by taking the concentrations of seven characteristic gases dissolved in the oil as inputs