In automotive industry,production speed and quality have been enormously improved.However,it is difficult to maintain the productivity while effectively detecting defects in complicated components such as planetary gear sets,which contain numerous elemental gears.Furthermore,accurately diagnosing a specific fault type among various fault types is an even more challenging issue in practice.In this research,we develop a data driven model based on artificial neural network(ANN) to diagnose the condition of planetary gear sets,which potentially have several fault types.The transmission error is measured to represent the condition of the planetary gear sets.ANN is employed to detect various fault types.