Simulating Eddy Current Sensors in Blade Tip Timing Application: Modeling and Experimental Validation Conference Paper uri icon


  • Copyright © 2018 ASME. In gas turbines, the blade vibration caused by aerodynamic excitation or by self-excited vibration and flutter leads to high cycle fatigue that represents the main cause of damage in turbomachinery. Turbine operators have resorted to assess the blade vibrations using non-contact systems. One of the well-known non-contact methods is Blade Tip Timing (BTT). BTT is based on monitoring the time history of the passing of each blade tip by stationary sensors mounted in a casing around the blades. The BTT method evaluates the blade time of arrival (ToA) in order to estimate the vibration. To perform the BTT technique, optical sensors were widely used by industry due to their high accuracy and performance under high temperatures, but the main drawback of these systems is their low tolerance to the presence of contaminants. To mitigate this downside, Eddy Current Sensors (ECS) are a good alternative for health monitoring application in gas turbines due to their immunity to contaminants and debris. This type of sensor was used by many researches, predominantly on the experimental side. The focus was to extract response frequencies and therefore the accuracy of the timing measurement was ignored due to the lack of modeling. This paper fills the gap between experiments and modeling by simulating a BTT application where detailed finite element modeling of active and passive ECS outputs was performed. A test rig composed of a bladed disk with 12 blades clamped to a rotating shaft was designed and manufactured in order to validate the proposed models with experimental measurements. Finally, a comparison between these different types of sensor output is presented to show the effect of the blade tip clearance and rotational speed on the accuracy of the BTT measurement.

author list (cited authors)

  • Jamia, N., Friswell, M. I., El-Borgi, S., & Rajendran, P.

citation count

  • 0

publication date

  • November 2018