Corrosion fatigue life prediction method based on BP neural network and application

The invention relates to a corrosion fatigue life prediction method based on a BP neural network and application. The prediction method comprises the following steps: selecting maximum stress, stress ratio, loading frequency and pH value of a solution as main factors influencing corrosion fatigue life; designing and processing a corrosion solution circulating device matched with a corrosion fatigue test, and carrying out a corrosion fatigue circulation failure series experiments on a high-strength sucker rod sample in a specific production environment, collecting and neatening experiment data and dividing the experiment data into training samples and prediction samples; setting artificial neuron network parameters, and establishing nonlinear mapping between the influencing factors and the corrosion fatigue life; training and testing a nervous system; and predicting the corrosion fatigue life of a new sample. The corrosion fatigue life prediction method based on the BP neural network has the beneficial effects that the corrosion fatigue life of a high-strength sucker rod is predicted by high non-linear approximation capability of the BP neural network model, and operation is simple; and the prediction method is high in generalization performance, and engineering application is facilitated.