USE OF MULTIPLE VARIABLE MATHEMATICAL METHOD FOR EFFECTIVE CONDITION MONITORING OF GAS TURBINES

摘要

All over the globe, gas turbines (GTs) play tremendous role in energy and power generation. Condition monitoring is also being used to obtain early warning of impending equipment failure to prevent costly downtime and damage to process equipment. Several scheduled visits were thus made to AFAM IV, GT 18, TYPE 13D plant located near Port Harcourt, in Rivers State of Nigeria. Continuous and periodic monitoring of the thermodynamics/performance parameters such as temperature, pressure, air pumping capability and fuel flow were carried out. These activities lasted for over a period of one year on hourly basis to examine the state of health of the engine compared with the data taken. The diagnostic method of trend performance monitoring was jointly used with multiple variable mathematical models (MVMMs), because they relate deterioration to consequences. A software code-named "THAPC0M" written in C++ programming language was used proactively monitor the engine based on this MVMMs. Thevalues observed on the third month revealed that Vj0 was27.0% and AL was 48MW. A significant variation in the results obtained shows that there is a deviation between the monitored data taken from the console and the reference data in the manufacturer's manual. These are indications of impending failure or health uncertainty of the engine. This allowed maintenance to be scheduled, or other actions taken to avoid catastrophy.