Fault monitoring and diagnosis in mining equipment: current and future developments

Abstract

The authors survey monitoring and diagnosis technologies which offer opportunities for improving equipment availability in mining. They briefly present a framework for comparing and contrasting different techniques, and examine the application of expert systems and knowledge-based methods to mining applications. Model-based methods are discussed from the viewpoint of both analytical models and qualitative models. Neural nets and other pattern recognition techniques are described. The special problems of monitoring and diagnosis that mining poses are discussed, and the relative benefits of the various methods are summarized.<>