J. Sottile et Le. Holloway, AN OVERVIEW OF FAULT MONITORING AND DIAGNOSIS IN MINING EQUIPMENT, IEEE transactions on industry applications, 30(5), 1994, pp. 1326-1332
Proper detection and diagnosis of failing system components is crucial
to efficient mining operations. However, the harsh mining environment
offers special challenges to these types of actions. The atmosphere i
s damp, dirty, and potentially explosive, and equipment is located in
confined areas far from shop facilities. These conditions, coupled wit
h the increasing cost of downtime and complexity of mining equipment,
have forced researchers and operators to investigate alternatives for
improving equipment maintainability. This paper surveys monitoring and
diagnosis technologies that offer opportunities for improving equipme
nt availability in mining. Expert systems, model-based approaches, and
neural nets are each discussed in the context of fault detection and
diagnosis. The paper concludes with a comparative discussion summarizi
ng the advantages and disadvantages of each.