Gear Fault Diagnosis with Support Vector Machine

Because of the complexity of gear working condition, there are non-linear relationship between characteristic parameters and fault types. This paper proposes to apply the Support Vector Machine to set up the nonlinear mapping to solve the difficulties of gear fault diagnosis. Taking a certain gearbox fault signal acquisition experimental system for instance, Matlab software and its neural network toolbox are used to model and simulate. The simulation result shows the founded model has preferable learning and generalization capabilities, which performs effectively in the common gear fault diagnosis and it can identify various types of faults stably and accurately.