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ArticleName Reduction energy prediction for layer-type cone crushers
DOI 10.17580/or.2019.05.01
ArticleAuthor Elnikova S. P., Gazaleeva G. I.

«Uralmekhanobr» JSC (Ekaterinburg, Russia):

Elnikova S. P., Researcher,
Gazaleeva G. I., Head of Department, Doctor of Engineering Sciences,


A methodology and an algorithm were developed for predicting the specific energy consumption in layer-type crushing of materials in cone crushers, including the establishment of the analytical law for respective particle size distribution, the energy-size ratio, and the reduction probability function. Industrial tests for a KMD-2200T7-D layer-type crusher were completed with the establishment of its performance indicators. As a result of processing the test data, it has been shown that the Godin–Andreev law may be used to describe the particle size distribution of the crushing product and that the Rosin–Rammler law may be used to describe the crusher feed characteristics. The function has been obtained that characterizes the probability of reduction of material particles of various size classes in the mix. A mathematical model is proposed for calculating the specific energy consumption during layer-type crushing, taking into account the distribution law, the probability function, and the energy-size ratio. A program has been developed that allows increasing the number of iterations when calculating the integral. The values of reduction energy obtained in actual practice, calculated using the model, and estimated by the Bond formula have been compared. The results indicate that the specific energy consumption values obtained using the proposed model are close to the experimental data, while the Bond formula calculations render overestimated predicted energy consumption values. The optimal crusher operating mode has been established using the three key criteria of specific power consumption, yield of commercial-grade gravel fractions, and allowable content of flaky grains in the gravel fractions.

keywords Layer-type crushing, specific power consumption for reduction, particle size distribution characteristics, Bond index, reduction probability for particles in layer-type crushing, optimal crusher operating mode

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