Blade health monitoring of gas turbine using online crack detection

Abstract

Gas turbine engine blades are subjected to severe fatigue which is caused by complex in-service environment. In fact, blade crack is one of the costliest sources of damage in gas turbine. Detection of cracks of blades is important to ensure safe and reliable operation of gas turbine engine. A vibration-based damage-detection methodology is presented in this paper to monitor the health condition of gas turbine rotor blade. In order to simulation the real-time dynamic crack propagation of rotor blades, model analysis was performed using a finite element model to calculate the natural frequencies and mode shapes of gas turbine blade, the possible crack initiation location was determined, the natural frequencies and mode shapes changed as the crack growing, indicating the feasibility of the methodology to capture the dynamic health condition of blade on-line. Simulation results have indicated the capability of the methodology in evaluating the changes of blade vibration signals once damage is initiated of growing, and in consistently detecting cracks of damaged blade to monitor the health condition. Additionally, the results indicated that blade natural frequency decays slightly when crack propagating, providing the potential for reliable diagnosis of the gas turbine blades with crack fault, thus the implementation of blade health monitoring system will be the approach to achieve condition-based maintenance.