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In this study, the fault diagnosis of nonlinear gearbox is investigated by using the frequency domain approach. The Nonlinear Output Frequency Response Functions (NOFRFs) of the nonlinear gearbox are evaluated and be used to diagnosis the abnormal conditions of the gears and the bearings. A case study is used to illustrate the NOFRFs based feature extraction method, then a probabilistic neural network (PNN) is mentioned to classify the failure modes. Finally, the results show that this method can complete the fault diagnosis of gearbox perfectly. The study provides a basis of the application of the NOFRFs and PNN in the fault diagnosis or condition monitoring of complex nonlinear systems.

Fault diagnosis of gearbox based on the nonlinear output frequency response functions and PNN