关键词: 加速寿命试验, BP神经网络, 寿命预测, 多应力, 可靠性

Abstract: To deal with the difficulties of traditional life prediction methods in establishing an accelerated model and solving pluralism likelihood equations, a new model is proposed to predict the life of the items in multi-stress accelerated life testing(ALT) based on the back propagation (BP) artificial neural network (ANN). The accelerated stress levels and reliability are used as training input vectors. By the least square fitting, the regression equation of the original data can be obtained, with which a large number of simulation data can be generated as training target vectors. Then a threelayer BP neural network is set up and trained, and failure data can be predicted by putting the normal stress levels and required reliability into the model, and the predicting curves can be drawn. Comparison with the simulation data demonstrates that the model can reflect the relationships among the stress levels, the reliability, and the life of the items. It provides a new route for life-prediction in multi-stress accelerated life testing.

Key words: accelerated life testing, BP neural network, life prediction, multi-stress, reliability