The invention discloses a
methanol synthesis catalyst performance online prediction and health management method. The method comprises the following steps: S1, obtaining three groups of
time sequence data of reactor
inlet temperature, outlet gas CO2 concentration and reactor pressure; s2, the three groups of
time sequence data are input into a pre-trained LSTM neural
network model, an input layer of the LSTM neural
network model comprises three nodes, a
hidden layer of the LSTM neural
network model comprises 128 nodes, an output layer of the LSTM neural network model comprises one node, and the LSTM neural network model is used for outputting a catalyst activity predicted value; and S3, when the predicted value of the catalyst activity is lower than 85.0%, triggering an early warning
signal. According to the method, the catalyst
performance prediction response delay and the
false alarm rate are greatly reduced, the service life
utilization rate of the catalyst is also improved, hardware modification is not needed, dependence on internal data of the catalyst is completely avoided, and high-benefit and zero-risk intelligent operation and maintenance are realized.