Industrial equipment health trend analysis method and system based on ARIMA and LSTM algorithms

The invention relates to an industrial equipment health trend analysis method and system based on ARIMA and LSTM algorithms. The method comprises the following steps: 1) acquiring running state information data of industrial equipment through a sensor; 2) preprocessing the acquired data, removing noise data, and ensuring the availability and accuracy of the data; 3) performing feature selection onthe preprocessed data; 4) utilizing an ARIMA model to predict the change trend of a single feature in the features obtained in the step 3); 5) inputting the prediction result in the step 4) into theLSTM model as training data, and training the LSTM model; and 6) inputting historical data of the industrial equipment into the trained LSTM model to obtain a prediction result of the health trend ofthe industrial equipment. As a support technology for operation and maintenance of key components of an intelligent factory, the method can realize analysis and prediction of the state trend of the equipment, realizes intellect