The application of AE measurement for condition monitoring of the slow-speed and heavy-load equipment is gaining ground. However, different AE features are sensitive to fault in varying degrees when they are employed in the trend analysis. Therefore, in this paper the focus is on the selection of the appropriate AE features for the trend analysis. First the AE features are ranked by Laplacian Score method according to their importance, and then a new feature index is obtained by the fusion of the features with their ranking scores, which serve as weight coefficient in this condition. The degradation data of the bearings in the belt conveyor are used to prove that the proposed method is effective.