A Method for Accurately Predicting the Stress Relaxation of Springs

The application of spring mechanism is very wide, from daily life to industrial manufacturing, spring mechanism plays an important role, but with the accumulation of working time, the spring can fail due to stress relaxation, leading to potential safety hazards. Therefore, in addition to improving the stress relaxation resistance of the spring through heat treatment and other methods, the stress relaxation should also be accurately predicted when the spring system is working. Based on the temporal series of spring stress relaxation data and long short-term memory (LSTM) network algorithm, this paper predicts spring stress relaxation by bidirectional long short-term memory (Bi-LSTM) network and bilayer LSTM model, respectively. At the same time, the prediction results of the two are compared to obtain the most accurate prediction scheme.