Gear fault diagnosis using transmission error and ensemble empirical mode decomposition

Classification of spall and crack faults of gear teeth is studied by applying the ensemble empirical mode decomposition (EEMD) to the transmission error (TE) measured by the encoders of the input and output shafts. Finite element models of the gears with the two faults are built, and TE's are obtained by simulation of the faulty gears under loaded contact to identify the different characteristics. A simple test bed for a pair of spur gears is prepared to illustrate the approach, in which the TE's are measured for the gears with seeded spall and crack, respectively. EEMD is applied to extract fault features under the noise from the measured TE. The differences of the spall and crack are clearly identified by the selected features of the intrinsic mode functions based on the class separability criterion. The k-nearest neighbor method is applied for the classification of the faults and normal gears using the features. The proposed method is advantageous over the existing practices in the sense that the TE signal measures the gear faults more directly with less noise, enabling successful diagnosis.