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The measured capacity of the crusher was computed as the daily output pided by the number of hours the crusher was run that day. The crusher is a secondary crusher. When designing a crushing plant the components are generally over-dimensioned and the plant bottleneck is placed late in the process. This means that the rest of the plant, at times will be under-utilised, and the crusher may not be choke fed. The measured capacity hence fluctuates. This is the reason why the capacity is generally over predicted.
During some shifts, the plant was set to crush 0–90 material in the secondary crusher, and during those shifts readings of power and hydroset pressure were not taken. Those shifts are not representative for the most common use of the machine,which is set to crush 0–90 mm material less than 10% of the time.
4. Discussion
The aim of this study was to improve the crusher model by adding a shear force dependent component in the wear model.As mentioned, in a previous study, there was a discrepancy between simulation and measurement in the upper part of the chamber .In the study by Lindqvist , an enhanced flow model was presented and the prediction of power draw, capacity and hydroset pressure improved considerably. There was a slight improvement in prediction of wear for a fine crushing chamber. When running simulations with the new flow model on a coarse chamber, it became apparent that the under-prediction in the upper part of the chamber was even worse (see Fig. 11). The disagreement between the model and measurement was thus more pronounced for the coarse chamber, where the nip angle between the liners is larger. The conclusion is that the inaccuracy in the previous flow model was not what caused the discrepancy, even though there was an improvement in prediction of other operating parameters.
Another proposed mechanism that could explain the discrepancy is that wear is dependent on particle size and number of contact points that occur. Furthermore, the rotation of the mantle deviates from ideal rolling against the rock in the upper part of the crushing chamber (see Fig. 5). None of these effects however, are likely to be more pronounced in a coarse chamber than in a fine crushing chamber, since the mantle does not differ much between the chamber types. The shape of the concave however, and the nip angle between the liners does indeed differ between the chamber types (see Fig. 6). Therefore this issue was addressed first.
An important question is whether the model parameters described by Lindqvist and Evertsson , remain valid as liners are worn. The measured power draw and hydroset pressure fluctuates considerably (see Figs. 15 and 16). These fluctuations cannot be explained by wear; consider for example readings during August when power draw and hydroset pressure is higher than during the rest of the period. No corresponding trend in capacity can be seen. The likely reason is that the properties of the rock have changed during this time. The rock is blasted and hauled to the crushing plant from different locations in the pit,and rock properties generally differ between different locations.
The crusher was not run choke fed at all times. This explains the under-prediction of capacity (see Fig. 17). During less than 10% of the crushers operating time, it was set to crush 0–90mm material, which means that capacity, power draw and hydroset pressure all increase. Readings of hydroset pressure and power draw were not taken for those operating conditions. The wear may change the geometry in a different way during that time. These periods of different operating conditions, less than 10% of the time, were neglected in the Simulation.
5.conclusions and future work
By adding a shear force dependent factor in the wear model for cone crushers, the agreement between simulated and measuredworn geometry was significantly improved.The prediction of operating parameters hydroset pressure and power draw was satisfactory, but measured power draw and hydroset pressure fluctuated. As was mentioned in previous sections, there are other possible explanations for the addressed model discrepancy,for example, the particle size distribution or non-linear relationships between wear rate and pressure. The crusher model used in this study can be described as a “grey-box” model. Introducing more model parameters to describe more phenomena might eventually make the problem of finding optimal model parameters poorly conditioned. Even though the model presented here, has successfully solved the addressed problem, further