The impact of system tribology on automatic control of cone crushers

Abstract

Cone crushers are a family of secondary and tertiary rock crushers used in the mineral processing and aggregate industries. The quarrying industry in the UK alone produces some 250 MTonnes of aggregates per annum for use in the construction industry.

Conventional cone crushers utilise on/of control which is based on personnel observation and manual off-line adjustment of the machine setting. The adjustment is effected mechanically or via a control panel and electrical means. This process involves long machine and plant down-time and can result in an inconsistent product due to drift in the machine setting caused by continuous wear of the liners used in the crushing chamber.

The impact of tribological parameters on the real-time control of cone crushers and a mechatronic solution to enhance and automate the control system is reported. The system employs a combination of intelligent sensors, predictive mathematical models and AI technology to provide real-time information on a number of system parameters. The information is utilised by a cascaded adaptive control system to maintain the correct cone crusher setting for optimum system performance. The improved control strategy is estimated to result in an annual saving of around £30 million in the UK alone.

Keywords

Adaptive control cone crusher system automation fuzzy modelling tribology

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