Abstract
This paper reports a mechatronics solution for the automation of a cone crusher control system. The system design is based on a network of intelligent sensors and actuators, artificial intelligence technology and adaptive control. Knowledge-based system (KBS) technology is used to define the optimum operational parameters which are maintained by an adaptive control system. A number of innovative wear sensors and predictive mathematical and fuzzy models are used to forecast the wear rate and profile under different operational and environmental conditions. On-line diagnostics and fault analysis are provided by another KBS module. The system architecture is modular and based on distributed processing and intelligence. The seamless integration capability of the modules offers a progressive sophistication in technology which allows the automation to phased in as required.
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