Features Linear Fusion Based on AP Clustering and AASC Algorithm

In the field of mechanical fault diagnosis, in order to improve the diagnosis accuracy with high feature dimension, a method of features linear fusion method based on AP(Affinity propagation clustering) and AASC(Affinity Aggregation for Spectral Clustering) algorithm was proposed. Low dimension space was obtained by AP clustering, then using AASC algorithm to fuse this selected features, and gained a new feature, meanwhile which can be used independently as a new feature. In the phase of experiment, this method was compared with respectively LPP and PCA, it’s result indicates that this method is excellent in improving diagnosis accuracy.