Identification of pick wear state based on acoustic emission and D-S evidence theory

In order to realize the intelligent monitoring of wear state in the cutting processes,the device of acoustic emission collected signal when the picks cut different proportions rock.The signals were decomposed and reconstructed via three-layer wavelet package.The pick wear was intelligent identified via D-S evidence theory.The result shows that the energy were concentrated in the bands 12.5～25.0 kHz and 37.5～50.0 kHz,and it decreased with the increase of pick wear state.Therefore,the energy ratio of two bands in total energy were selected as characteristic value to build the sample space.Under the combination rule of the four conditions,the intelligent identification accuracy is about 90%.This method provide a theoretical basis for grasping the picks wear state accurately,changing picks timely,improving the efficiency of mining machines and realizing intelligent mining.