A.M. Elzahaby, A. Khalil, Z. Zyada, M.M. Elmaadawy, and R.I. Fahmy (Egypt)
condition monitoring, preventive maintenance, ferrographic analysis, fuzzy synthetic decision-making.
In this paper, an evaluation of the gas turbine bearing situation near and under temperature alarm is presented. A fuzzy synthetic decision-making system is used as a predictive maintenance procedure to make diagnosis by ferrographic analysis for real data taken from a turbine bearing. Analyzing the wear debris, the bearing failure start is detected which gives an accurate view about bearing failure mode, however, using the temperature and vibration monitoring for bearing failure detection gives alarms at late stages of bearing failure. It is known that there is a time interval between bearing failure start and shutdown action due to temperature rise. The developed technique detects the start of bearing failure, so, the bearing can operate under known temperature alarm condition. As a result of the developed technique, the bearing life is divided into three areas, normal, caution and danger. Through the caution interval a suitable maintenance plan is done to avoid the emergency stop during dangerous zone. Hence the emergency stop due to temperature shutdown signal is changed to plan stop, which reduces the emergency cost and shutdown time and consequently increases the turbine availability.
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