Four common oil analysis techniques

namely Ferrography analysis

Spectrometric analysis

Particle count analysis

and Oil chemical-physics analysis

were used together with the engine test data to develop the fusion diagnosis method of engine wearing fault based on Neural Networks (NN) and D-S evidence theory.Firstly

according to standard wear limit

original data were transformed into BOOL value.Then

each sub-NN structure was established

and their training samples were obtained based on expert experience.After each sub-NN was trained successfully

the intermediate diagnosis results were obtained through each sub-NN.Finally

the NN diagnosis results are used as the basic probability distribution value to each fault mode

and the D-S evidence theory is applied

and the final fusion diagnosis results are obtained.An example was used to verify the method presented in this paper.