Title page for ETD etd-06102012-040513


Type of Document Master's Thesis
Author Kar, Tapas Ranjan
URN etd-06102012-040513
Title Fuzzy logic-based fault diagnosis for mining equipment failures
Degree Master of Science
Department Mining Engineering
Advisory Committee
Advisor Name Title
Topuz, Ertugrul Committee Chair
Adel, Gregory T. Committee Member
Lucas, L. R. Committee Member
Keywords
  • Machine theory
Date of Defense 1989-12-11
Availability restricted
Abstract
Equipment availability is the most significant factor in the productivity of many mines and

processing plants. Machine breakdowns are not only expensive in terms of production losses

but also important in meeting production schedules. In a complex piece of machinery like a

shearer or a powered support system in a highly automated longwall face, such breakdowns

can be due to one of the large number of possible faults. A large proportion, up to 80% of

the down time is spent in locating the fault. For this reason, a need for an automated diagnostic

method to assist the operator in the diagnosis process is felt. In this study, a diagnostic

system is developed by modeling the partially known or imprecise relations and poorly defined

variables found in a diagnostic environment. Logic of fuzzy sets and systems theory

finds an interesting application in this area. This study presents a diagnostic algorithm, which

relates the possible causes of failure to their respective symptoms through fuzzy logic paths.

Applications of the diagnostic method are illustrated through examples of a compressor and

a shearer.

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