The ability to identify faulty equipment under severe conditions allows the manufacturers and operators to take appropriate proactive measures to rectify the faults and provide an assessment for early detection of the engine defects that could lead to catastrophic failure. This work therefore shows that such counter measures can be carried out by optimization, modeling, simulation or using a reliable analysis of gas turbine engine, rotor shaft and bearing vibration data through 2-Dimensional D’Alembert’s equation. Gas turbine plants on industrial duty for electricity generation were thus used to actualize the research. The data for vibration amplitude of rotor bearings from the reference engine which varied between 0.19 and 3.81 mm/s were compared with those obtained from a failed engine of similar characteristics just before failure and used for the simulation and modeling. The given engine speed and active load were also determined as falling between 7264 rpm to 7436 rpm and 10 MW to 20 MW respectively. A well packaged computer program code-named “MELBF” written in C++ programming language was developed. The results show that the machine should not be run beyond 3.81 mm/s vibration amplitude in order to avoid resonance and downtime of the engine.

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