Aiming at the online wear condition monitoring of a mining reducer for engineering applications,the relationship between wear debris features and wear status is studied.Firstly,ferrograph images are firstly captured by using an online wear debris image acquisition system.Secondly,the wear particle features are extracted by utilizing digital image processing technology,where the Otsu’s automatic thresholding method is employed to separate wear particles from the image background,and the debris features of relative concentration and the maximum width are extracted using a pixel scanning method.Finally,the wear status of a mining reducer is analyzed based on the statistical features of online wear debris.Additionally,the experiments are carried out and the results demonstrate that the proposed method is effective to monitor a running machine.This study also provides a new approach for automatic monitoring and intelligent maintenance of mining reducer.