Variable-pitch motor abnormal temperature rise early warning method combining TF-IDF and LSTM models

The invention discloses a variable pitch motor abnormal temperature rise early warning method combining TF-IDF and LSTM models. The method comprises the following steps: data extraction: extracting corresponding measurement point data from a fan SCADA historical database; data cleaning: removing the data of each measuring point according to a corresponding principle; fan working condition division: during model training, training different models for different loads to obtain different baseline values; a TF-IDF model and an LSTM model are adopted for training, and a function relation is trained to describe the temperature change of the variable-pitch motor; and running the early warning model: running the model once every hour, and finally mapping the model into an early warning level. According to the method, the abnormal temperature rise of the variable-pitch motor is detected by adopting a technology of combining an abnormal detection model constructed by adopting a symbolization representation technology