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 AbstractEquipment 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
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