Abstract:

In order to overcome the difficulty of modern missile equipment fault forecast, which is induced by the complexity of system composition, fuzziness of configuration connection and incomplete and uncertaint character parameters, according to data fusion technique and grey forecast theory, a new forecast method based on data fusion and improved multi variables metabolism unequal interval weighted grey model (IMUGM(1,m,w)model) is proposed. Firstly, multi variables unequal interval weight grey model(MUGM(1,m,w)model) is built by introducing weight gene and optimized by initial value optimization, residual error correction and metabolism．Then the specific individual’s historical measure data are used as the benchmark, and the same kind of products and the specific individual’s corresponding forecast values are calculated using IMUGM(1,m,w)models. The Euclid distances are used to determine degree of membership, so the individual’s performance degradation model is built on the basis of the degree of membership weighted method. Finally, the measurement data, Euclid distances, degree of membership and performance degradation model are updated with real time measurement data. The proposed method is applied to fatigue crack growth data, and the experimental results validate the validity. The result of simulating practical missile equipment fault forecast and analysis validates the validity.