Forecasting model for degradation path and parameter estimation based on neural network

Traditional life evaluation theory established on the basis of mass failure data, the phenomena of little or naught failure put forward challenges for existed life evaluation theory. The performance degradation data provide useful information for products´ reliability and gives feasible way for products´ life evaluation. The limitations of existing degradation models are analyzed, a new forecasting model and parameter estimation method based on neural network is brought forward. By using back propagation neural network(BPNN), the nonlinear degradation path of product performance can be got, and the parameters can be estimated by self-adaptive neural network. An example is given out to validate the effectiveness of the method and compared with existing model.