###### Abstract  
Cone crushers are used in the aggregates and mining industries to crush rock material. The pressure on cone crusher liners is the key factor that influences the hydraulic pressure, power draw and liner wear. In order to dynamically analyze and calculate cone crusher performance along with liner wear, a series of experiments are performed to obtain the crushed rock material samples from a crushing plant at different time intervals. In this study, piston die tests are carried out and a model relating compression coefficient, compression ratio and particle size distribution to a corresponding pressure is presented. On this basis, a new wear prediction model is proposed combining the empirical model for predicting liner wear with time parameter. A simple and practical model, based on the wear model and interparticle breakage, is presented for calculating compression ratio of each crushing zone along with liner wear. Furthermore, the size distribution of the product is calculated based on existing size reduction process model. A method of analysis of product size distribution and shape in the crushing process considering liner wear is proposed. Finally, the validity of the wear model is verified via testing. The result shows that there is a significant improvement of the prediction of cone crusher performance considering liner wear as compared to the previous model.  
c pacs: 42.50.-c, 42.50.  
particle size distribution index. [PERSON] [14] performed experiments based on full factorial design adopted from statistical modelling software, and the input parameters like load, sliding distance, hardness of coal, and hardness of liner material are taken into consideration, and weight loss was considered as the output response. [PERSON] and [PERSON] [15] introduced the method of calculating the compression ratio and the pressure distribution angle of each crushing zone, which were key parameters for calculating the distribution of the pressure on the liner. In addition, a wear model was developed by [PERSON] [16]. Recently, wear prediction using Discrete Element Method (DEM) was proposed [17] with a wear model to predict wear on the liner of a mill, obtaining very good agreement using an abrasion measure as the wear predictor. [PERSON] and [PERSON] [18] present computational simulation results of a new DEM breakage model for an industrial cone crusher. The model incorporates non-spherical particles represented as superquadrics, which are broken based on the compressive energy at a contact into non-spherical progeny particles. [PERSON] [1] presented a wear function with data obtained from an actual crusher operating at gradually increasing CSS. Therefore, it is very meaningful to further study the effect of liner wear on cone crusher performance.  
The main objective of the present work is to investigate how the liner wear affects cone crusher performance using the crushing plant test. A model relating a coefficient of material hardness, compression ratio and particle size distribution to a corresponding pressure is presented. Then, combining the empirical model for predicting liner wear with time parameter, a new wear prediction model is proposed. The model is important for predicting cone crusher performance along with liner wear. This work can be used for improving cone crusher performance. In addition, this paper describes a method for modelling cone crusher performance along with liner wear. The results of crushing plant test are compared with the corresponding results from the prediction.