Hydropower station monitoring alarm event intelligent identification method based on deep learning

The invention discloses a hydropower station monitoring alarm event intelligent identification method based on deep learning, and the method comprises the steps: collecting hydropower station monitoring historical data, carrying out the cleaning of the data, obtaining a pure data set, building a user dictionary and a stop word table according to alarm information, carrying out word segmentation, stop word removal and word drying processing on the data set based on the user dictionary and the stop word list, and training by utilizing a natural language processing technology to obtain word vectors of all corpora; and establishing a knowledge rule, constructing an event sample library, inputting the event sample library into a bidirectional long-short-term memory network classification model for training to obtain a deep learning model capable of completing alarm event autonomous intelligent identification, and taking the output of the model as an event identification result. According to the method, second-leve